Stories of women leaders in AI

Gail Blum

Manager, Talent Acquisition

Operations, NBCUniversal, USA

Patricia Maqetuka

Chief Data Architecture & Operations Officer, Nedbank, South Africa

Elenita Elinon

Executive Director Quantitative

Research, JP Morgan Chase &

Company, USA

Christine Gabbard

Project Manager, Machine Assistance,

Autodesk, USA

Fernanda Gonzalez

Digital Channels Manager,

Banco Santander Rio, Argentina

Tanuja Singeetham

Vice President, Marketing,

BEHR Paint, USA

Rupinder Dhillon

Director, AI and Machine Learning,

Bell Canada, Canada

Lorna Russell

Senior Manager, Product Management,

BMC Software, USA

Walkiria Schirrmeister Marchetti

CIO, Bradesco, Brazil

Keiko Konno

General Manager, Service Planning & Development Division, Bridge International, Japan

Maren Reinsch

Head of Sales & Services,

DB Dialog GmbH, Germany

Siewchoo Soh

Managing Director,

DBS Bank, Singapore

Claudia Pohlink

Head of Artificial Intelligence, Deutsche

Telekom/ T-Labs, Germany

Dr. Xiaojun Huang

Senior Advisor Upstream Digital

Transformation, ExxonMobil, USA

Donna Hill

Assistant Director, Service, Configuration & Continuity Management, George Washington University, USA

Victoria Stasiewicz

Global Information Systems –

Manager Information Management,

Harley-Davidson, USA

Kyoka Nakagawa

Chief Engineer, Value Creation Department,

Digital Transformation Division, Honda R&D Co., Ltd., Japan

Sara Hines

Director of Provider Experience &

Connectivity, Humana, USA

Hye-young Kim

Director of Artificial Intelligence,

LOTTE Shopping, South Korea

Yimei Guo

Managing Director, Global Head of

Research Technology, Morgan Stanley, USA

Sandra Cascadden

Associate Deputy Minister/CIO,

Government of Nova Scotia, Canada

Severine Marquay

AI experience, digital support &

innovation, Orange France, France

Rachel Cordrey

Pharmacy Supervisor, Peninsula

Regional Medical Center, USA

MaryAnn Fleming

Head of Services, Home Buying and Ownership,

RBS, UK

Erin Oles

Senior Director, R+F Virtual Live, Rodan

+ Fields, USA

Carolyn Staats

Director of Innovation, Information Systems Department, Sonoma County, USA

Lee Hatton

CEO, UBank, Australia

Laura Bellamy

Director, Information Experience,

VMWare, USA

Shelley Kalms

Chief Digital Officer, Woodside Energy,

Australia

Claudia Ignacio

Executive Director Client Experience,

Banco Mercantil del Norte (Banorte), Mexico

Harmeen Mehta

Chief Information Officer & Head Cloud

and Security Business, Bharti Airtel,

India

Sabine Scheunert

Vice President Digital & IT Sales/Marketing

Mercedes-Benz Cars, Daimler, AG, Germany

Ona Juodkiene

Co-Head of IT Operations, Danske

Bank, Denmark

Jaki Lynn Van Valin

Director Data Management & Analytics,

Harley-Davidson, USA

Seema Gaur

Executive VP & Head IT, IFFCO Tokio

General Insurance Company, India

Kelly Combs

Director, Emerging Technology Risk,

KPMG LLP, USA

Carmen Suarez

Assistant Director, Miami-Dade County,

Florida, USA

Jennifer Edgin

CTO, Deputy Commandant Information,

U.S. Marine Corps, USA

Tanja Richter

Director, Consumer Products and

Services, Vodafone, UK

Dr. Yu-Ching Lan

Project Manager, Big Data and Cyber Security Division, IT Center, Walsin Lihwa Corporation, Taiwan

Gail Blum

Manager, Talent Acquisition Operations,

NBCUniversal, USA

Patricia Maqetuka

Chief Data Officer,

Nedbank, South Africa

Elenita Elinon

Executive Director of Quantitative Research,

JP Morgan Chase

Elenita has led JPMC’s pioneering deployment of machine learning in the area of investment banking model risk control operating on massive, highly complex financial datasets, a large-scale workstream withJP Morgan Chase’s investment banking businessand technologies.Elenita's projects are part of JPMC's extensive machine learning and artificial intelligence efforts,with applications ranging from hedging strategies to trading to the critical area of detecting fraud, led by their AI practitioners with backgrounds in academia and tech.

What was the opportunity you sought to address with AI?

Model risk control is a critical function in the investment bank. Stricter regulations have led to an abundance of restrictions, model reviews, testing,and monitoring on models used in trading. Model risk data and and workflows need to be efficiently handled thru automation and accurate analysis, identifying the correct actions to apply once an event is identified. AI can have a significant role in enablingpattern discovery (fraud, issues), issue classification and categorization, data qualityidentification andremediation, and overall reduction of the cost of doing business. That involves a complete end-to-end solution, from development to deployment of machine learningmodels.

What advice would you share with others who are considering using AI?

Find a problem to solve first—talk to your stakeholders and understand their pain points. Then evaluate all possible solutions, including non-AI. Consider the total cost of ownershipof an AI solutionand make sure it’s sustainable and that results are trustworthy and explainable to stakeholders.

What do you believe is most critical to making an AI project successful in driving business results?

Understand the use casesand get agreement with the users on the measures for success. AI can be a part of the complete solution. Understand the end-to-end strategy and design flexibility without over-engineering. Get lots of immediate feedback, and develop in an agile way.

What’s the best advice you’ve ever received?

Make opportunities for yourself–don’t wait to get themhanded to you. How? Talk to people, get feedback, ask for help, don’t accept the status quo, ask questions, challenge, don’t expect to solve everything yourself—and look forthe best in your network.

Christine Gabbard

Project Manager for Artificial Intelligence and Machine Learning,

Autodesk

Christine has transformed Autodesk’s customer service by integrating Watson Assistant into the company’s support platform, reducing wait times and costs, and improving customer satisfaction.

What was the challenge you sought to address with AI?

Back in 2016, our customer support organization received one million cases per year, which cost the company anywhere between $13 and $200 per case. Our average customer satisfaction rate was at 65%, with growing wait times and a shortage of live support agents. With our move to a subscription model and direct digital sales, we needed a sustainable, scalable model. We decided to revolutionize the way we support our customers and create an experience where they actually want to engage with us. We partnered with IBM to explore their Watson platform, and have since evolved the initiative into a fully operational program.

What benefits are you realizing with your organization's use of AI?

AVA (Autodesk Virtual Agent) launched in February 2017, and her popularity as a customer support solution took even the team that developed her by surprise. Historically, our customers have waited up to two days on average for an agent to provide a solution --our agents are busy! AVA can solve easier cases in less than two and a half minutes. This has freed upour agents to focus on tougher, more complex issues.

What do you know now that you wish you’d known when you started this project?

It is crucial to understand the criteria for selecting use cases that are most likely suited for AIvirtual agents—they should be high volume, high frequency, easy to solve manually, and less complex customer questions. Also, there is more return on investment if our team focuses on improving the use cases that AVA can handle well, rather than adding more scope to the dialog capabilities.

What is something other than AI that you’re passionate about in your life?

If I had a side hustle or if I changed careers, I’d become a career coach. I find it very rewarding to help people find their path and I am a strong supporter of mentorships. I have a dream of starting an internship program for professionals already in the workforce who want to change careers!

Fernanda Gonzalez

Digital Channels Manager,

Banco Santander Rio, Argentina

Tanuja Singeetham

Vice President, Marketing,

BEHR Paint, USA

Tanuja was the driving force behind Behr’s new Color Discovery tool, a mobile app that helps consumers choose a paint palette by asking them how they want their home to feel. Home improvement projects can be overwhelming, but by using Watson to offer personalized color recommendations, Tanuja hopes to make the prospect of painting a room a little less daunting.

What was the challenge your organization sought to address by using AI?

Choosing a paint color in a home improvement store can be overwhelming. There are so many colors to choose from. Design shows, magazine articles and Pinterest projects can all inspire consumers, but can also add to the paradox of choice. This often keeps people from moving forward with their projects and can be a barrier for sales. Our big goal is to provide tools to help people find their perfect color.

How are you using Watson in your business?

We researched the relationship between colors and feelings, and built the Color Discovery tool on our website. The tool has been very successful, but was limited in reach since it was only on our site. With IBM Watson, we were able to embed the tool within a mobile app so consumers could use it while choosing a paint color at home, in a store or on the go. Watson used natural language processing, tone analysis and extensive training on Behr colors to deliver a customized color palette for each consumer.

What benefits are you realizing with your organization's use of AI?

Brands like Amazon, Netflix, Spotify and others have raised the bar on consumer expectations. We know consumers don't want a one-size-fits-all solution. For brands to stay relevant and offer meaningful value to consumers, we have to build products and solutions based on their individual needs. AI allows us to use consumer input to offer the personalized recommendations they are seeking.

Rupinder Dhillon

Director, AI and Machine Learning,

Bell Canada, Canada

Lorna Russell

Senior Manager, Product Management,

BMC Software, USA

Lorna is BMC Software’s Watson champion. She has worked with IBM to integrate Watson into BMC's Helix platform, combining two powerful cognitive technologies into one valuable product. Lorna has also helped BMC’s clients implement Helix in services like chatbots that are smart enough to field complex user inquiries.

What do you believe is most critical to making an AI project successful in driving business results?

Start small. Many organizations make the mistake of launching large-scale, multi-pronged initiatives with too many complicated or unclear objectives. Those projects fail. Instead, before kicking off any project, identify opportunities for improvement first. Once you have a clear understanding of your objectives and the problems you need to solve, that is when you should evaluate whether AI is the right tool to achieve a positive business outcome.

What do you wish you knew when you first started with your work with AI that you know now?

I didn't realize how much fun following AI developments would be! AI is developing so fast and seems to be speeding up exponentially. As AI services mature, they are offering us an opportunity to solve business problems more efficiently than we have ever been able to do in the past. On the other hand, AI still requires a lot of human interaction like training—you are automating processes, but also developing new roles and jobs to enable that automation. Like many, I thought AI could teach itself. I now know that this isn't always the case.

Any other professional passions besides AI?

IT is my second career. I used to be a field archaeologist, but found that you can't support a family on an archaeologist's salary, so I took an interest in technology and convinced a company to hire me, which started me on the road to product management.

Walkiria Schirrmeister Marchetti

CIO,

Bradesco, Brazil

As the CIO of one of Brazil’s largest banks, Walkiria has overseen the development of Bradesco’s virtual assistant, Bradesco Inteligência Artificial. Initially designed as a Q&A system for internal employees, BIA now answers questions consumers may have about bank products, making Bradesco the first Brazilian bank to implement AI in a customer service setting.

How are you using Watson in your business?

IBM reached out with a commercial proposition for Bradesco to use Watson back in 2015. We knew that was the appropriate moment for this promising technology and jumped right in. Now, Watson is the AI engine behind our digital assistant BIA. As of March 2019, BIA has surpassed 100 million interactions.

What’s been the biggest surprise about integrating AI into your business?

Our most pleasant surprise was the responsiveness of the new technology. Every time we push Watson to its limits, it gives us back more. For example, when we first tested Watson on understanding the Portuguese language, we introduced variations such as slang, regionalisms, abbreviations, prolixity and even vulgar language. Even so, the results were better than expected.

What advice would you share with others who are considering using AI?

Artificial intelligence is only possible with human wisdom. So treat your people well. Artificial means that it is made by people, and people with the right combination of skills to develop AI are not abundant these days. Ideally, working with AI requires the technical knowledge of a data scientist, the savviness of a teacher, and the ability to translate highly technical information in ways that others can understand. This requires good communication skills and the ability to work with colleagues on a team. It’s no wonder that most of our core team have been reskilled in-house. Those with technical backgrounds had to acquire soft skills and vice-versa. So far, we’ve managed to keep the team very engaged. But we know that there is a growing need in the market for professionals with this experience, so we treat our employees well.

Keiko Konno

General Manager, Service Planning & Development Division,

BRIDGE International Corp.

Bridge International is the leading inside sales service provider in Japan. Keiko is the technical leader who introduced Watson into her company in the form of an AI-based system that helps salespeople navigate business-to-business sales calls via telephone and e-mail. The AI system helps enhance sales skills for newcomers and less experienced staff. As a result, the company can open up more employment opportunities for people who are interested in sales, but haven’t much sales experience.

What was the challenge you sought to address with AI?

We offer outsourcing, consulting and tools to B2B companies, including those in the IT, communication, distribution and manufacturing industries. In recent years, it has become difficult to hire and develop highly skilled salespeople due to labor shortages. Taking advantage of the AI technology, we can coach our salespeople to enhance their skills and better serve our clients.

Why did you choose Watson for your business?

Our AI-based call navigation system, Sales AI Navigator or SAIN, makes suggestions for what salespeople should say to clients in real time during B2B outbound calls. We chose IBM Watson because of its speech-to-text engine and natural language classifier. Watson speech-to-text engine was the only AI that recognized client’s speech at an 80 to 90 percent accuracy rate. Outbound calls require the AI engine to be highly flexible, with a high learning capacity. Watson was the right choice.

What benefits are you realizing with your organization's use of AI?

AI can help our salespeople better serve our clients, which leads to the success of our clients’ business. Because AI SAIN has started helping our salespeople, our productivity has gone up by 47 percent. We believe that we will be able to expand sales employment opportunities for people who require flexible work styles, such as for childcare and elder care.

What advice would you give to the next generation of women as they enter the workforce?

I think women have more opportunities to play an active role in the area of cutting-edge technologies including AI. Look at business opportunities, be proud of yourself, and speak up actively. Our company gives equal opportunity regardless of gender and age—we give priority to those who are taking on new challenges in spite of fear of failure. By our products and challenges, we want to contribute to society, such as offering support for human resources and expanding the number of women employees.

Maren Reinsch

Head of Sales & Services,

DB Dialog & DB System, Germany

Siewchoo Soh

Managing Director, Head of Consumer Banking and Big Data/AI Technology,

DBS Bank

Siewchoo has led DBS Bank, a Singapore-based multinational banking company, toward taking advantage of AI both internally and in customer-facing channels. In addition to using AI in a customer service domain, DBS has introduced Hiri, a Watson-based virtual assistant designed to help answer employee questions without human intervention, additionally DBS also using various Watson APIs and services in their multiple markets.

What was the opportunity you sought to take advantage of with AI?

We are a customer-obsessed organization. As such, we always begin solving problems for our customers by understanding their everyday needs and pain points. So far, we have used AI to understand more about our customers and employees, but now we are also looking to completely change banking using AI. For example, we are working on using AI and big data to deliver tailor-made solutions to our customers in real time. We also want to use AI to make a sustainable impact in our community by reaching those who don’t have access to formal financial services.

What benefits have you realized with AI so far?

Our first AI-driven virtual assistant now handles more than 80 percent of requests on Facebook Messenger accurately without human intervention. We also deployed AI to transform our employee experience. Since the launch of our Watson-backed employee assistant Hiri, more than 7,000 employees have received answers to more than 40,000 questions. Similarly, we transformed our recruitment journey using another AI initiative. Since the launch, we have increased our reach fivefold, the amount of time needed to screen candidates has been reduced by 75 percent, and candidates’ drop-off rate has decreased from 15 percent to three percent.

What’s the best advice you’ve ever received?

The best advice I have received is to be yourself and not modify your character or values to conform to the norms of your environment. For the generation of women who are entering the workforce now, I would say that this is the time to seize the moment. Take hold of the opportunity to pursue what you are passionate about and have no doubts about the impact you can make.

Claudia Pohlink

Head of AI/ML,

Telekom Innovation Laboratories, Deutsche Telekom AG

Since T-Labs has established AI as a core innovation area in 2017, the research facility of Deutsche Telekom is one of the most active players in AI in Berlin. Claudia’s team focuses mainly on the use of AI methods, such as machine learning (ML), in network-relevant use cases focusing on emerging next generation communication networks like 5G and automation of core-network capacity planning. In addition, she’s involved with Quantum AI, collaborative robotics and AI in the Internet of Things. Coming from a Data Science background, she is also very interested in the data privacy and transparency discussion.

What opportunity were you trying to address with AI?

Our ambition behind AI projects is driven by the potential for automation and improvement. This applies to all core processes in the telco business, where AI helps to increase quality, speed and accuracy–especially looking at our highly complex network operations. What is often surprising to me is the versatility of AI: We can apply our methods to many different business problems and come up with improvements.

What do you wish you knew when you first started your work with AI that you know now?

There is a lot I learn every day about AI, and the whole public and scientific discourse is moving fast. Looking back, it would have been really helpful to be able to look two years into the future and see where to focus with all the different tools, methods and ideas would have moved.

What advice would you give to the next generation of women as they enter the workforce?

Speak out, be proud of your achievements and don’t hide. Try to be open and learn a lot every day about the things that most interest you. Doing all of this enabled me to shape my field of responsibility within T-Labs, so that I am able to work within the area I am most passionate about now.

Dr. Xiaojun Huang

Senior Advisor Upstream Digital Transformation,

ExxonMobil

Xiaojun and her team are using AI to create a CT-like scan of inner earth. This will help ExxonMobil target drilling investments on the most promising opportunities, adding speed and precision, and minimizing human biases. The current project focuses on deep-water drilling off the coast of Guyana.

What are you looking to achieve with AI?

We are at the early stages of transforming our work processes. Our goal is to allow our domain experts to focus on what they’re good at, augmented with AI. The project allows for much more efficient and collaborative planning for Guyana deep water development wells. Ultimately, that will lead to an ever-safer operation and steep improvements in efficiency and profitability.

What are some key things that you’ve learned?

We need to change the way we approach our business processes and partnership. Transformation is not about moving every piece of data to the cloud, it is rather about re-imagining work processes inside out through the lenses of the art of possibility with all digital technologies, with a focus on business objectives. Digital transformation requires agility and speed. We established our collaboration agreement with IBM, put together the team in a month, and delivered the minimum viable product to the Guyana team in 10 months.

What do you wish you knew when you first started with your work with AI?

We need to have empowered digital champions to help transform a large organization. Understanding both the business and AI, these champions can connect business with solutions, advocate principles and value for change, and act as conduit between the organization and external innovations. I strongly advise that key business champions to get their feet wet on AI.

What advice would you give to the next generation of women as they enter the workforce?

Be brutally honest with yourself about your strength, passion and areas for improvement. Follow your heart, work hard, learn fast and be curious.

Donna Hill

Assistant Director, Service, Configuration & Continuity Management,

George Washington University, USA

Donna introduced a chatbot trained to answer questions and solve technological problems anytime and anywhere—up to 60% of student help desk issues can be automated, allowing students to get help on their schedule.

What challenge are you trying to overcome with AI?

The university operates in a decentralized environment with departments that use different systems to perform operational and service functions. This puts the onus on the students to determine what their problem is, who is responsible for the solution, what department they need to contact and what tool they need to use to submit a request. As you can imagine, this is no easy task. We are using Watson as part of an integrated solution that enables self-service through a chatbot we call Martha.

What benefits are you seeing from your project?

Our main goal for implementing AI was to improve the customer service experience by connecting studentsto answers as efficiently as possibleand we’ve done that. We are now able to offer students the ability to make a service request by simply texting Martha--no human intervention required. And given the data gathered during the proof-of-concept phase, we are anticipating a 45% deflection of tier 1 tickets from our call center, creating a substantial savings that can be used to resolve higher level support issues.

What advice would you share with others who are considering using AI?

Understand your audience and its idiosyncrasies. People approach questions very differently. It is easy for humans to make conversation using all of their senses, but AI does not have that ability and relies on keywords and training to make those connections. If a chatbot is not trained to consider the various ways a question can be asked, then the value of the output goes down. In addition to slang, it is important to have a diverse testing committee to ensure that unconscious bias has not been inadvertently programmed into the chatbot.

Victoria M. Stasiewicz

Manager of Information Management,

Harley-Davidson Motor Company

Victoria have helped steer Harley-Davidson into the 21st century by taking advantage of a number of AI capabilities. With a suite of technologies that includes Watson Studio, they have helped the iconic motorcycle company integrate cutting-edge technology into its business model. Thanks to their leadership, the world of the future will have internet-connected motorcycles.

What have you learned and what advice would you share with others who are considering using AI?

I learned that a full discovery phase is key to success; and conducting that prior to formal project planning is a best practice. Ensuring that readiness target dates are accurate and concise and that everyone is in agreement is also key.

What advice would you give to the next generation of women as they enter the workforce?

Inspect what you expect and if you see people catching up to you, it is time to run faster. I would like to tell the women of the next generation to not worry about hitting the throttle and to take the path that appears a little rougher. Without challenge we cannot grow and without growth humankind cannot enter the next century prepared to handle the challenges our environment will place upon us.

Kyoka Nakagawa

Chief Engineer, Value Creation Department, Digital Transformation Division, Digital Solution Center, Honda R&D Co., Ltd., Japan

Kyoka is leading Honda R&D’s efforts to train its automotive engineers to use advanced IBM Analytics tools, helping them to better understand driver behavior, to increase the reliability of cars, and to design a more personalized driving experience.

What was the challenge you sought to address with AI?

The challenge was to raise our engineers’ interest in wanting to use other people’s data that could enhance their analysis. I offered an open proof of concept for people who have different engineering expertise for data they had never used, which helped engineers imagine how they can enlarge their analysis capability with other sources of data.

What benefits are you realizing?

Teaching AI helps people to organize their own thinking and their processes, and to help focus their core of knowledge. It was a surprise to me that when AI functions well at work, business people seem to create more ideas to do better work. It may be because AI helps unburden some of their workload.

What do you wish you knew when you first started with your work with AI that you know now?

AI planning requires special skills, and not every project ends in success.

What’s the best advice you’ve ever received?

Push the frontier, and open the way to go where you want to go. Enjoy being a woman and a mother while you become an important person at work. Get in touch with a lot of great people at work. There are lots of learning opportunities outside of schools and your own workplace.

Sara Hines

Director of Provider Experience & Connectivity,

Humana, USA

Sara led the development of a virtual agent to answer questions for the medical practices and hospitals calling into Humana. The goal was not just to answer their questions, but to capture the outcomes, metrics and perceptions of these interactions—and to build a smarter system. The Watson AI Virtual Agent pilot is handling live calls with 120 practices, answering questions such as, “I need to understand if a vaccine is covered” or “I’d like to check speech therapy benefits.”

What have you learned in your work with AI that you wish you’d know in the beginning of the project?

To develop an AI organization that has a holistic, governed approach, all internal teams across the enterprise need to support, endorse and drive towards this organizational structure.

What advice would you share with others who are considering using AI?

The irony is that both the AI continuously learns through its experiences and so do the individuals supporting AI. I am always learning something new, even after decades of working with the technology. My advice is to always be open to learning and never stop exploring the infinite possibilities of AI.

What do you believe is most critical to making an AI project successful in driving business results?

Understanding AI is different than any other technology in the market. It needs to have a full agile team working together to tend to the ever-evolving nature of this type of platform. This is not the type of technology that you set up and walk away. It needs monitoring, training and supervising to harness the true insights that can be brought forth. I believe to make an AI project successful is to understand the nonlinear nature of this technology and embrace the art of the possible.

Hye-young Kim

Director of Artificial Intelligence,

LOTTE Shopping, South Korea

Hye Young is leading projects that are transforming the shopping experience for customers of LOTTE eCommerce, one of Korea’s largest retailers.

What was the opportunity you were working to address with AI?

After analyzing the market, we found that new players with disruptive technology were penetrating the traditional market, so we wanted to use advanced analytics and AI to improve our business competitiveness.

How are you using Watson?

With Watson, we were able to integrate channels to help our distribution service in our first AI project. In our second project, we created a trend prediction system that used internal and external data on point of sale, weather, buyer’s age (and more) to help us develop new productions.

What have you learned that you wish you knew when you first started working with AI?

I want to tell people to get started first. If you wait for all the data to be collected, the project will never begin. But once you start the project you soon know what data is needed and how to collect it. Let me emphasize once more: just get started!

What advice would you give to the next generation of women as they enter the workforce?

First, try without fear. Second, don’t be too afraid. Third, I want to say that if you don’t try because you’re afraid of failure, you don’t have a chance.

Yimei Guo

Managing Director, Global Head of Research Technology,

Morgan Stanley

Yimei has been a driving force for applying AI and machine learning at Morgan Stanley in three critical ways: digital transformation, innovation, and as a champion for diversity.

What was the opportunity you sought to address with AI?

There is an enormous amount of data in the financial industry that can be harnessed to deliver value for the business and for our clients. AI and machine-learning solutions have the potential to generate insights, improve client experience and increase organizational efficiency. For example, we are using predictive modeling to deliver relevant investment insights to our clients; we are optimizing the search experience in our Research portals with machine learning and natural language processing so clients can find the right information in the least amount of time; and we built a virtual assistant to provide quick answers to routine questions.

What are some of the key things that you’ve learned?

There are considerable opportunities to use AI and machine learning to extract meaningful data from vast amounts of unstructured data and generate business signals. The key success factor is the close partnership among domain experts, data scientists and data engineers. Business domain knowledge is essential as machine-learning models are very specific to each industry. Off-the-shelf vendor products will not be accurate for the financial industry. It’s critical that these products are open, and that models can be re-trainable with industry-specific data.

What advice would you give to the next generation of women as they enter the workforce?

My advice is to be curious. Curiosity is key to understanding the world around you and to ensure that you continue to evolve professionally. Whether it’s starting a new job or embarking on a new project, you need to be open to navigating new cultures, listening to diverse view points, and taking new approaches.

Sandra Cascadden

Associate Deputy Minister/CIO,

Government of Nova Scotia, Canada

Sandra oversees the government’s information and technology systems. She’s also responsible for looking into the future for the best new tech to employ to make the government services more efficient, while ensuring continued support of legacy systems.

How are you using Watson in your business?

One of our departments needed to improve the monitoring and evaluation of one of its programs, and have access to data to make better evidence-based decisions. Hundreds of submissions were made to the program monthly, and they were either paper-based or in electronic spreadsheet format. It was impossible to effectively evaluate or report on the activities and the outcomes of the program. We used Watson to analyze the reports and assess patterns, flag misalignments, and predict future behaviors.

What benefits are you realizing withyour organization's use of AI?

Working with AI makes you start thinking differently. We humans can only assess a certain amount of data but with AI the more data you can feed it the more insightful the findings are.

What advice would you share with others who are considering using AI?

First, make sure AI is the right solution. Then start small—really small. Grow the solution slowly. Also, start with something that’s easy. Don’t go for the most complex decisions right away.

What do you believe is most critical to making an AI project successful in driving business results?

AI has to solve a real business problem, and you need to remember that there will be a lot of learning along the way. Plus, there are lots of new things to think about, for example, the ethical use of AI in making decisions and how we have to be prepared to demonstrate that the coding and algorithms are unbiased.

What else are you passionate about in your life?

I am passionate about solving problems to help people and make their lives better. Whether that is as small as streamlining a process all the way to introducing big technology changes that are innovative and rock the world.

Severine Marquay

AI experience, digital support & innovation,

Orange France, France

Séverine is creating effortless, fast and personalized experiences for Orange France’s customers.

What was the goal you set out to achieve with AI?

Our goal is to provide an effortless, fast, and personalized customer experience, one that is aligned with our security requirements, as well as our IT processes. We started small and specific, using a test-and-learn approach. We wanted to know if our customers were happy with the content the bot provided.

What benefits are you realizing with your organization's use of AI?

AI projects enhance the benefits of agile methodology that we have put in place. Everyone works together, analyzing customer conversations and feedback to make the best decisions to feed the bot. You can’t do AI if you don’t know your customers, as well as your operational and IT processes.

What have you learned and what advice would you share with others who are considering using AI?

You have to know what you want from your AI project. Start small and grow fast. Focus on one use case or one small team. Also, choose open-minded people who are willing to challenge themselves, learn and take quick decisions in agile ways. Having technical expertise is important, but passion, customer understanding and the knowledge of your company processes are keys.

What advice would you give to the next generation of women as they enter the workforce?

You can live different lives in one professional career; make it your own and keep on learning. Learning and understanding are my key drivers in life!

Rachel Cordrey

Pharmacy Supervisor,

Peninsula Regional Medical Center, USA

Rachel led the deployment of Micromedex, a drug information database, which helps nurses and pharmacists provide better care to patients at Peninsula Regional Medical Center—the first hospital to integrate Watson Assistant into its use of Electronic Health Records. Last year, Watson handled more than 100,000 questions related to medications, dosage and interactions that could affect patients.

What benefits are you realizing with AI?

Watson streamlined our workflow and allowed us to find answers to medication-related questions much faster and more easily than traditional search methods, which is critically important for patient care. For example, a nurse can ask Watson for the IV compatibility of two medications instead of calling a pharmacist or digging through a traditional IV compatibility tool online. This is increasing patient safety and making it easier for us to care for patients.

What have you learned that you wish you knew when you first started working with AI?

I wish I had understood how quickly the tool would develop and learn—and the IBM team did a great job incorporating feedback and teaching Watson things like common spelling mistakes and medical terminology in just a few short months. It was unusual for us to see that amount of progress in such a short time span.

What advice would you share with others who are considering using AI?

We should all start thinking about where AI can help improve the work you do each day. AI is not meant to replace us or our jobs. It’s a tool to help us perform our jobs better.

What do you believe is most critical to making an AI project successful in driving business results?

As with any project, you have to have a strong multidisciplinary team. It takes a group of diverse thinkers to incorporate something so impactful into daily work. It can be difficult to understand early on how much a tool like this is able to provide; it is critical to set reasonable expectations. You may not be able to solve all of the problems immediately.

What advice would you give to the next generation of women as they enter the workforce?

Take opportunities when they present themselves and put the work in to achieve results.

MaryAnn Fleming

Head of Services, Home Buying and Ownership, RBS, UK

MaryAnn and her team developed the first paperless mortgage process in the UK, and have doubled mortgage lending in the past five years. At the center of this transformation is a natural-language agent known as Marge. Powered by IBM Watson, Marge answers the agents’ questions and assists with compliance issues, giving them more time to focus on their customers.

What was the opportunity or challenge you sought to address through AI?

There’s increased regulation in the UK mortgage market, which creates more complexity for our agents. In simpler times, agents could rely on their knowledge and memory. But that was no longer a viable option. We required a solution that would allow our agents to truly listen to and understand our customers without the pressure of having to remember what the next step in the process was going to be.

How are you using Watson in your business?

Marge, powered by Watson, supports our agents by delivering all updates to their desktop in real time. The system also generates data, which we can then analyze to deepen our understanding of the customer journey and the opportunities that exist to make improvements.

Have you found anything surprising or transformational in the process?

The surprising element comes with our people. We had the nervousness that there could be a lack of trust in AI from agents on the frontline. This could not have been further from the truth—the agents have embraced Marge as a trusted colleague and have been active in her education to allow them to better support their customers.

What advice would you give to the next generation of women as they enter the workforce?

Set a clear vision, know your purpose and stand by your values. For me, I asked myself what success would look like for me when I was 60. Then work back and develop an inclusive work/life plan.

Erin Oles

Senior Director, R+F Virtual Live,

Rodan + Fields, USA

Erin and her team work with IBM’s Watson Media to share personalized offers for Rodan + Fields Customers via immersive videos and live video streaming with the brand’s Independent Consultants.

How are you using Watson in your business?

We’ve worked with IBM Watson Media to create R+F Virtual so that our Consultants across the globe can get a virtual front row seat during R+F conferences via live streaming, and access to hundreds of hours of educational video content. The platform helps R+F Consultants live stream their own content and convert more prospects with quick links to shop while watching, and content is automatically enriched with Watson AI to help ensure Consultants can search and find what they are looking for in seconds. Our vision is to combine our data with the best AI-driven analytics to create an exquisite experience for the customer.

Can you share some key things you’ve learned from working with AI?

Personalization is a journey, requiring a strong foundation and an appetite for test and learn as you hone your biggest opportunities. Our Consultants choose to participate in this business for many different reasons and for most, this is not their full-time job. Not only does our tool need to provide value but it has to be easy to fit into the nooks and crannies of their day, as you’ll often find them working other jobs, balancing kids and family priorities or cramming for finals. If they can’t find value within the first few moments of interacting with our tool, we missed our opportunity.

What do you wish you knew when you first started with your work with AI that you know now?

Focus on what’s core to your business objectives and continue to come back to that. Small AI wins in the right targeted direction can create huge impact.

What advice would you share with others who are considering using AI?

Be focused and intentional. There’s a limitless opportunity to learn from AI insights, but don’t sacrifice progress because of your insatiable curiosity to know everything.

What advice would you give to the next generation of women as they enter the workforce?

Consider the leader you want to be and embody that from the beginning. Empathy, aptitude for personal relationships, and intuition are all undervalued professional skills that are female strengths. Grab your seat at the table and don’t give it up just because you’re inclined to accommodate. The opportunity is yours. Nobody will fight for you if you don’t fight for yourself.

Seek out companies, teams, bosses that embody what it means to empower female leadership. I’m inspired by strong female leaders, like our Founders, who set a high bar for creating a life-changing opportunity for women worldwide, and I feel connected to that mission every day.

Carolyn Staats

Director of Innovation, Information Systems Department,

Sonoma County, California

In the aftermath of devastating fires, Sonoma County continues to serve the community, and Carolyn is leading a team that is using data and AI to bring together information from wide-ranging departments and produce more effective and powerful help for people who need it.

What was the challenge you sought to address with AI?

We knew intuitively that our most vulnerable population was probably being served by multiple departments at the county, but we had no way to prove it nor any mechanism to analyze their needs across multiple programs.

What benefits are you realizing?

Because Watson Care Manager provides a 360-degree view of a client, it allows, for the first time, our front-line staff across the Safety Net departments to collaborate for the most effective care of their clients. With Connect 360, we have mastered client records across health and social services, behavioral health, housing and justice systems providing vital and timely information in one location for case managers to access. Watson Care Manager is fabulous not only because it provides a central point for client information but also because it is agile, mobile and cloud based, enabling us to meet our clients where they are.

What do you wish you knew when you first started with your work with AI that you know now?

When I first started this work with AI, my frame of reference was big data analysis, machine learning, etc. I really did not think about how useful AI could be in simple, even common situations such as helping a client make it to their doctor appointment, local clinic or housing assistance.

What’s the best advice you’ve ever received?

Don’t be afraid to fail...and don’t be afraid to let others fail. It’s often the best source of learning and provides the very means of moving forward.

Lee Hatton

CEO, UBank, Australia

Lee Hatton’s team at UBank has worked with IBM over the past two years to create innovative, automated customer service products. It started with RoboChat, to help customers with their home loan applications, and then RoboBrain, to centralize resources for UBank’s own customer service advisors. The latest innovation is Mia, a virtual agent that can answer hundreds of different questions in realtime, transforming the online experience and creating a one-to-one personal connection with each customer.

How are you using Watson in your business?

We first started in the AI space in 2017, working with the IBM Watson team. This was to solve a customer problem: the application form was sometimes overwhelming to people. So, we set out to build RoboChat, a text-based chatbot, in about eight weeks. This now gives customers support at any time with the home loan app, and it also frees up our advisors to help customers with more complex questions during business hours. Now we’ve developed Mia, which can answer more than 300 different spoken questions, which we built in partnership with IBM and FaceMe.

Once we had really aced something for our customers, we wanted to use AI to do something for our team members. They used to have to search multiple sources for something as simple as our current interest rate. So, we ingested 950 documents across four sources to create RoboBrain. Now, our advisors can type in a question on the dedicated RoboBrain web page and the answer is shared with them in real time. It’s a one-stop portal of valuable information to help us deliver a faster customer and employee experience.

What have you learned that you wish you had known when you first started working with AI?

You're never going to get to a perfect moment with AI—by its very nature, it will always continue to learn the more it interacts with customers. Don't be afraid of that journey. Embrace it and take your customers along with you. Also, it’s critically important to not lose sight of the problem you’re solving. It’s easy to get wrapped up in the technology and the excitement of doing something new, which is great, but you need to think about why you’re doing it and never stray from that focus.

What advice would you give to the next generation of womenas they enter the workforce?

You're going to get some less than stellar advice. I once had a male leader tell me that my team and I were too ambitious and running too fast and that I needed to "come back down from the mountain" and join the rest of the team on a slower journey. And while you never want to leave people behind, don't let someone else's insecurities stop you from achieving greatness. Be bold and help people understand your vision for the future.

Laura Bellamy

Director, Information Experience,

VMWare, USA

Laura and her team developed a virtual assistant and incorporated it into their portals to help customers find answers. With a wealth of content available, making queries easier and more effective has the potential to be a big differentiator in improving the customer support experience.

What benefits are you realizing with your organization’s use of AI?

Machine learning has helped to bridge the gap between the way we talk about our products and the way customers do. We’ve realized what a corporate asset machine learning models can be to improve our own operations. We see the opportunity to establish centers of excellence, build a learning model catalog, and enable all teams in VMware to use these technologies for their own use cases.

What do you believe is most critical to making an AI project successful in driving business results?

In such a technically rich field, I think success is actually related to culture. Machine learning brings the opportunity to answer key questions for your business, but it also shows patterns and brings insights that you might not be prepared for. It’s important that your team trusts the data used to build the model and has confidence in the model predictions, so they are prepared to trust the insights and the results that machine learning might deliver.

What’s the best advice you’ve ever received?

A boss once told me: “Don’t try to improve the things you aren’t good at. It takes a lot of time and wastes your talent. Instead, focus on what you love and what you are good at. Double down on those skills because they will do the most good and bring you the most joy.” In a time when you are expected to be great at everything, you can be a domain expert, be an inspirational leader, and be a nurturing parent, but choose for yourself where you want to excel. I've learned that I want to be good enough at most things and be exceptional in a few things I care most about.

Shelley Kalms

Chief Digital Officer,

Woodside Energy, Australia

Having developed more than 18 use cases for AI in health, safety and much more at Woodside, Shelley and her team are pioneering AI integration in their industry.

What was the opportunity you sought to address with AI?

This is about a team effort in unlocking the collective intelligence of our organization—both past and present. It’s about enabling and empowering our people, and making their jobs better by giving them the right information sooner, generating insights and actions to improve our business. In this way, we will become a true learning organization.

What benefits are you realizing?

Tasks that used to take weeks are now done in days, enabling our people to spend much more time on high-value tasks such as analyzing, interpreting and making decisions rather than collecting information. It’s now all at our fingertips.

What have you learned that you wish you’d known when you first started working with AI?

My own learning journey with AI is ongoing, but at this point I can reflect that being able to deliver a technically viable solution is only one part of the challenge. Embedding AI in how people work requires an investment well beyond project delivery, and that’s what we’re focusing on now.

What’s the best advice you’ve ever received?

Be brave, not perfect.

Claudia Ignacio

Executive Director Customer Experience,

Banorte Bank, Mexico

Claudia has been integral in promoting the expansion of AI to a new channel to serve the bank's clients as part of Banorte's transformation program Vision 2020, which includes an emphasis on investing innovation and technology to offer customers the best products and services, and support employees in maximizing their performance. With Watson's Virtual Assistant, Banorte began to offer clients a mechanism to serve them and to execute transactions in digital channels. The next challenge is to make it easy for clients to do business with ease through their digital banking, while providing the bank with the means to analyze the behavior of customers, adapt transactions and better meet their lifestyles.

What benefits are you realizing with your organization's use of AI?

Currently the number of customers served through Watson in digital channels is growing at a rate of 15% per month, Watson has responded to 1.2million customers. Watson has been learning a lot in a short period of time too, and customers’ confidence in using AI has been growing. Banorte has reduced calls to the contact center by 13% during 2019.

What have you learned while you have been using AI?

We have learned that AI is a key piece in the personalization and improvement of the customer experience, not only in digital channels, but also incall centers and helping employees in the branches.

What do you believe is most critical in making an AI project successful in driving business results?

Involving the organization in complex issues, such as AI, accelerates change. Employees have helped train Watson, and we’ve also involved customers in defining key transactions to help them become comfortable with Watson. These actions have been fundamental to the success of the program.

What advice would you give to the next generation of women as they enter the workforce?

In the path of life, you will find allies and obstacles—the important thing is to know where you want to go,work hard and to act honestly and responsiblyon the way.

Harmeen Mehta

Chief Information Officer & Head Cloud and Security Business,

Bharti Airtel, India

Sabine Scheunert

Vice President Digital & IT Sales/Marketing,

Mercedes-Benz Cars, Daimler AG

Sabine has helped Daimler integrate AI into multiple levels of the automotive company’s business. Under her leadership, Daimler has rolled out Ask Mercedes, a Watson-based customer service chat bot that has been able to replace about 60,000 phone calls per year. AI has helped Daimler become more efficient both on the customer-facing side of their business and in their internal operations.

What was the challenge you sought to address in your organization through AI?

Daimler is facing one of the biggest challenges in its history. Radical technological advancement, new players entering the market, and shifts in how people use mobility have all come together to create a disruptive force to this organization. We as a company have had to examine how we need to transform to thrive in the future. This has meant changing how we do business, sourcing untapped revenue streams, and shifting the way we work internally. Our vision is to become the digital champion of our industry. AI has been instrumental in helping us reach this goal.

What benefits are you realizing with Daimler’s use of AI?

Applying AI has helped simplify (and in some cases fully automate) processes that had previously cost significant time and resources. One example is an AI application that we use for airfreighting of our car parts. It is a complete bot automation that scans hundreds of daily emails of parts shipments, plus generates custom clearance reports at the border.

What have you learned since Daimler began using AI?

We have learned that exploring AI is fundamental to any organization. There is so much potential in simply investigating how AI can enhance the way you work, or the services and experiences you provide. The risk of being left behind is far greater than the commitment to learn, do and deliver.

Ona Juodkiene

Co-Head of IT Operations,

Danske Bank, Denmark

Ona leads Danske Bank’s digital transformation, aimed at achieving higher availability and reliability of Danske’s products and services—and ensuring that customer service constantly improves.

What was the opportunity you wanted to pursue with AI?

We are constantly seeking to improve the service our customers are receiving, so we are on a transformation journey to achieve higher availability and reliability of our services, as well as create innovative products. In terms of operational stability, we want to introduce the core capability of detecting and resolving incidents before they cause issues for our customers.

How are you using Watson in your business?

We are in the process of applying two products: Watson for IT Service desk where an AI-powered chatbot/virtual assistant will resolve IT issues for internal bank colleagues, and Predictive Insights to foresee IT outages before the actual customer impact occurs. We see both tools as key factors in making IT support faster, more automated and more efficient.

What advice would you share with others who are considering using AI?

Setting up AI technology takes time—and human brains. The quality of the output you get from the data is very much dependent on the data you put in. Highly skilled employees calibrate the system in an ongoing iterative process and help teach the system. It takes time and talented IT professionals to tailor and adjust and integrate these systems into the organization’s IT environment. But when you invest in this, it makes it possible to create a positive culture across the organization.

What’s the best advice you’ve everreceived?

I would say the best advice can be summed up in three main points: dream big, always learn and develop, and do not give up on your dreams. “Always learn and develop” is the most important to me. The biggest development achievements take a lot oftime and small incremental steps that are not visible on a daily basis. Only if we enjoy the learning process itself and keep doing that for a long enough time, will we realize how much we have achieved or how much we have changed.

Jaki Lynn Van Valin

Director of Data Management & Analytics,

Harley-Davidson Motor Company

Jaki have helped steer Harley-Davidson into the 21st century by taking advantage of a number of AI capabilities. With a suite of technologies that includes Watson Studio, they have helped the iconic motorcycle company integrate cutting-edge technology into its business model. Thanks to their leadership, the world of the future will have internet-connected motorcycles.

What have you learned and what advice would you share with others who are considering using AI?

Even though AI is shiny and new, it’s still all about the data. The quality of your AI insights depends on the quality and governance of your data. It is critical that your business teams and partners are involved in your efforts to provide clarity, cleanliness, and correct interpretations of the data. Although it sounds silly to use “AI” and “start small” in the same sentence, you’ll find greater success by failing, learning and then winning fast.

What advice would you give to the next generation of women as they enter the workforce?

Break the rules. In other words, question the norm and challenge the routine. Imagination supported by the strength to ask “why?” will lead you to greater success.

Seema Gaur

Executive Vice President and Headof IT,

IFFCO Tokio General Insurance Company

Seema and her team at IFFCO Tokio General Insurance Company are working to make it a lot easier for their customers to deal with vehicle damage claims with an AI-based mobile app, which helps settle claims quickly and easily.

How are you using AI?

We use AI to assess the claims of damaged vehicles through image processing. A customer can upload photos of the damage through a mobile app and the AI engine analyzes the photos and, within seconds, generates a list of needed repairable and replaceable parts. These parts are then searched in the historical claims database for the average cost of repairor replacement. The total cost is displayed to the customer on their mobile app within few minutes, and they can accept or reject the offer. If it’s accepted, payment is made through a payment service within a few minutes. The assessment data is also analyzed by a claims officer at the back office for verification purposes. Any discrepancies are sent as feedback to the AI engine to help it learn.

What benefits are you realizing with AI?

We have used the system for about two months and it’s resulted in a much better customer experience. We’re currently using it on about 20 car models, but we will add about 30 more in coming months. We will also extend this service to do pre-inspections of cars where break-ins occur. We have found this process to be truly transformational. The end-to-end claim settlement time has been reduced from three or four hours to just 15 minutes.

What have you learned that you wish you knew when you first started with your work with AI?

Proper data input is essential for machine learning, and continuous data feedback is essential to increase the accuracy of the AI engine.

What advice would you share with others who are considering using AI?

Machine learning requires perseverance. Be prepared with a comprehensive set of input information to the AI engine. Do a thorough proof-of-concept run with vendors before finalizing the product. Test the AI engine with varied input data to ensure accuracy. And run a parallel, human-assisted model to gain confidence in AI.

Kelly Combs

Director Emerging Technology Risk,

KPMG LLP

Kelly consults with businesses on responsibly implementing brand new technologies like AI and machine learning. She's currently working with IBM on using Watson OpenScale to help enterprises operationalize KPMG’s AI risk and controls framework. KPMG’s AI in Control is a comprehensive risk and controls framework that helps enterprise leaders plan, prepare, build and consume AI in the context of business operations. IBM Watson Openscale is software that helps organizations manage AI, with trust and confidence in the outcomes, once it’s been rolled out.

What has surprised you the most about the process of using AI?

All of the different stakeholders involved with the technology and understanding the stakeholders’ needs, concerns and requirements. What is inspiring, however, is how many conversations we’re having about how to govern and understand AI. These conversations are being encouraged at all levels even outside of traditional IT functions, signifying that this isn't just a passing trend, but a real shift in how we will be working with technology in the future.

What do you wish you knew when you first started working with AI?

I think a lot of us struggle understanding what we believe to be very complicated technologies. But just as much emphasis needs to be placed on understanding how we interact with technology, and how our skills and roles need to evolve as technology evolves.

What advice would you share with others who are considering using AI?

Don’t be afraid to leverage AI, but be thoughtful. Spend time understanding the benefits and the risks of AI to create an environment where people can trust in the technology.

What’s the best advice you’ve ever received?

"Don’t worry about when you will drop the ball, just make sure you don't drop the most important ball." This is important to keep in mind, especially as a consultant. My work is about continually evaluating what I’m doing and what is really the most important to me and my clients. You can't do everything, but getting the right things done within expectations is what matters. People will continually ask you to give more, so make sure you are focused and setting the right expectations based on what you can achieve.

Carmen Suarez

Assistant Director, Miami-Dade County,

Florida, USA

Carmen is the executive leader for one of IBM Watson’s first public sector local rollouts, which the county water utility uses to solve problems in its customer service division. Since that initial launch, use of Watson Assistant by the utility’s 400,000 customers has grown exponentially.

What was the challenge you wanted to address with AI?

Miami-Dade County Water and Sewer Department needed to reduce the overflow volume of calls placed in a queue to speak with an agent during business hours, and to expand service hours to customers who aren’t able to address any general billing questions and payment extensions options during off-business hours.

What advice would you share with others who are considering using AI?

When implementing any new technology that could have the perception of replacing human jobs, the business stakeholders that hold those existing jobs should be included in the process of re-engineering how the work gets done. This helps tame any fears that might generate passive resistance and hinder success. Find a business stakeholder champion to bridge gaps between the business and the IT professionals. Also, find a use case that has a meaningful effect on operations. Building the ability to log usage into the solution will allow you to provide visibility into value from day one.

What’s the best advice you’ve ever received?

Don’t be afraid. Technology is ever changing, and you will always be learning, teaching, collaborating, failing and then succeeding. Fear stifles the energy you’ll need.

Jennifer Edgin

CTO, Deputy Commandant Information,

U.S. Marine Corps, USA

Jennifer has helped the United States Marine Corps pursue a wide variety of AI implementations, from back-end business operations to field applications. Her goal is to continue to pair Marines with machines to be more effective both on the frontlines and behind the scenes.

How are the Marines using Watson?

Given the diverse mission set of the Marine Corps, we are pursuing many different approaches, and Watson is one of the many technical solutions that we have piloted. With Watson, we are looking at better ways to optimize the skill sets of the individual Marine, and to increase small unit performance by optimizing training events in the classroom and in the field. Traditionally this work had been completed by hand. Now, with Watson, we are unlocking new insights that we hadn’t discovered with manual processes.

What are you learning in your use of AI?

Each effort has provided an opportunity to learn how we want to employ a capability, to learn how we want to establish a continuous DEVOPS pipeline, and to learn even more ways that AI can assist Marines. The biggest thing that we have learned through each effort is that we are at the beginning of a transformational journey.

What do you wish you knew when you first started working with AI?

To embrace a philosophy of "just start" by picking a few pilot projects that solve a user problem, make business sense and have a fast execution timeline. The lessons that these pilots provide are critical to strategic growth.

Tanja Richter

Technology Director Consumer Products & Services, Vodafone Group Technology

In her work with Vodafone, Tanja has helped the telecommunications company integrate AI into its customer service system. Watson Assistant powers a virtual assistant that answers customer queries across a variety of platforms, including WhatsApp, Facebook and RCS. Tanja is now leading Vodafone into using Watson to build virtual agents that can speak to customers on the phone, reducing the time demands on liveagents while seamlessly integrating their skills.

How is Vodafone making use of Watson?

Watson is part of our central digital assistant framework that we are using in eleven markets to date. Our customer care chatbots support various channels, are linked to our customer care systems and integrated to relevant backend systems. To make the bot framework available in all markets and ensure reusability of components we use a digital abstraction layer. We started by using Watson to talk to customers via instant message, and we are now moving into voice interaction. Seamless handover to our agents is built into our system, making all the interaction histories available for agents. This helps us provide a better and more consistent customer experience in every interaction with our company, regardless of the channel our customer uses to approach us.

What advice would you share with others who are considering using AI?

Start small. Get your hands dirty by experimenting and scale only after you have a good grasp on the technology. Be clear from the beginning how you measure success: Start with a well-contained problem and don’t try immediately to save the world.

What advice would you give to the next generation of women as they enter the workforce?

Be yourself and build on your strengths. Believe in what you do, but at the same time, be open to advice. Invest your time in building networks and relationships.

Anything else you are passionate about, personally or professionally, that you would like to share?

When I’m not working, I love traveling, hiking and mountaineering. The highest mountain I’ve climbed is Acotango in Bolivia, which is 6,052 meters high. I love glacier tours in the Alps and also off-the-beaten-track trails in the UK, where I currently live.

Dr. Yu-Ching Lan

Project Manager, Big Data and Cyber Security Division, IT Center,

Walsin Lihwa Corporation, Taiwan

Yu-Ching is an executive with Walsin, a leading manufacturer of copper wires and rods, power cables, and specialty steel, and a leading real estate developer in Taiwan and East Asia. She has led the use of Watson’s text and data analysis capabilities to hire and train new staff, study market reports, and keep align different departments within the company. Her work with Watson has helped Walsin’s employees work more efficiently, saving time and money across all levels of the corporation.

What have you learned from integrating AI into your company?

We all know that the AI wave is coming. However, the use of AI should be based on the needs of the frontline workers. My company’s new AI program analyzed data from senior workers to help train new staff. During this program, we realized that everyone knows AI is important, but sometimes people don’t know what they want from an AI system. Finding what frontline users really need is the first challenge. Some people think that an AI system should be able to solve all their problems. Finding the bridge between people’s needs and the limits of the technology is the key to creating a great AI system.

What do you believe is most critical to making an AI project successful in driving business results?

I believe communication is most critical to making an AI project successful. Good communication helps people from different departments understand each other. Programmers need to understand the real need of frontline users, and users should help programmers design a better system. Good communication can save time and money for the company and its employees.

What advice would you give to the next generation of women as they enter the workforce?

Be a brave and honest person. Do the right thing. I’ve realized that when I choose the right path, other people with the same values will join in and we feel like an all-star team. Everyone helps each other and learns from each other. I think this is the reason I’ve been able to learn so fast in the AI field.