In the first and second part of this three-part series, we looked at definitions and use cases of generative AI. We’ll now explore the approach IBM Consulting takes when embarking upon AI projects. 

As business leaders investigate the best way to apply generative AI to their enterprise at scale, they need to consider trusted vendors and partners with expertise in data, machine learning and AI, data and AI governance, and proven capabilities of scaling applied AI within enterprises across industries and geographies. 

  • IBM Consulting has capabilities in Foundation Models delivery at scale. 
  • IBM Consulting brings industry expertise to understand the regulatory constraints and how to derive value with AI by augmenting specific workflows. 
  • IBM has close strategic partnerships to scale AI projects and has won many awards in this regard, including the US 2022 AWS Innovation Partner of the year.

The mission of IBM Consulting is to drive business transformation with hybrid cloud and AI in a way that is valuable and responsible. We formally stood up our AI Ethics Board in 2018 to ensure that AI systems created at IBM are developed and deployed ethically. The board is comprised of senior leaders from research, business units, human resources, diversity and inclusion, legal, government and regulatory affairs, procurement, and communications, who have the authority to direct and enforce AI-related initiatives and decisions.  

In the same year, IBM published its own principles of trust and transparency and offers them as a roadmap to others working with and implementing artificial intelligence. They focus on the following: 

  • The purpose of AI is to augment human intelligence;
  • Data and insights belong to their creator; and
  • New technology, including AI systems, must be transparent and explainable. 

These are the values by which we approach any work involving artificial intelligence: to enhance—not replace—human intelligence; to deliver client success without the requirement that clients relinquish rights to their data—nor the insights derived from that data—even when it is stored or processed by IBM; to provide clarity about who trains our AI systems, what data was used in that training and, most importantly, what went into an algorithm’s conclusions or recommendations. These principals are further supported by our defined pillars of trust, which we have dedicated time and resources to research, implement and disseminate:  

  1. Explainability: How an AI model arrives at a decision should be able to be understood 
  2. Fairness: AI models should treat all groups equitably 
  3. Robustness: AI systems should be able to withstand attacks to the training data 
  4. Transparency: All relevant aspects of an AI system should be available to the public for evaluation 
  5. Privacy: The data used in AI systems should be secure, and when that data belongs to an individual, the individual should understand how it is being used 

Generative AI and large language models (LLMs) introduce new hazards into the field of AI and we do not claim to have all the answers to the questions that these new solutions introduce. IBM understands that driving trust and transparency in artificial intelligence is not a technological challenge, it is a socio-technological challenge.  

80% of efforts in artificial intelligence get stuck in proof of concept for reasons ranging from misalignment to business strategy, to mistrust in the model’s results. IBM brings together vast transformation experience, industry expertise, proprietary and partner technologies and IBM Research to work with clients wherever they are on their AI journey. With this combination of skills and partnerships, IBM Consulting is uniquely suited to help businesses build the strategy and capabilities to operationalize and scale trusted AI to achieve their goals.  

Currently, IBM is one of few in the market that both provides AI solutions and has a consulting practice dedicated to helping clients with the safe and responsible use of that AI. IBM Consulting helps clients establish the organizational culture needed to safe-handle AI, build multi-disciplinary and diverse teams and think through risks and unintended effects. We work with businesses to identify low-risk uses cases, to assess, educate, and communicate across the organization and to stand up their own internal AI ethics board.  

IBM embraces an open ecosystem approach, working with IBM technology as well as a diverse set of ecosystem partners including AWS, Microsoft Azure, Google Cloud, Salesforce, and others, designing intelligence and productivity across mission critical workflows and systems. IBM Garage methodology co-creates, co-executes, and co-operates with enterprise teams to quickly ideate, pilot, test and scale projects. In the co-innovation phases, we employ ethics-driven exercises to ensure that our intentions match our actions.  

IBM can help companies put AI into action today to re-imagine workflows with AI, to automate end-to-end enterprise processes, to replace mundane tasks to achieve productivity gains with AI-driven decision making, personalize employee and customer interactions, and more. Our AI services include: 

  1. Analytics and AI to build, train and deploy AI and ML models for your business. We will work together to integrate bespoke models into your operations, continually revise and optimize them over time.  
  2. AI and Automation Advisory to integrate best of breed AI and Automation solutions for full stack observation and orchestration, driving highly automated and predictive IT Operations across business processes, applications and hybrid clouds. 
  3. Full-Service Automation to leverage IBM’s full suite of technology and services platforms that enables straight through “touchless” processing with minimal human involvement.

IBM has a number of resources to help you learn more about AI and Automation services including research about the open-source tools available to activate against trust & transparency and IBM AI Ethics. You can also learn more about this three-part series by reading the first or second installment, or reaching out to an expert for start a conversation about your needs.

Register for our webcast: What does ChatGPT mean for business? – How to drive disruptive value with Generative AI

More from Business Transformation

How IBM® and Esri are working together to map a more sustainable future

Businesses today have greater responsibility than simply making profits; they have a role to play in ensuring our planet remains livable for generations to come. Each year, we collectively release over 50 billion tons of carbon dioxide into the atmosphere, up 40% from 1990. Of these emissions, roughly 80% come from real estate, industry and transportation. If we’re going to succeed in sustainable development, actions must involve business owners. And businesses are responding. According to a 2022 survey of 3,000…

IBM named a Leader in The Forrester Wave™: Data Management for Analytics, Q1 2023

Accelerate your analytics transformation journey with IBM data management solutions The opportunity to work with many clients on their analytics journey inspires us to achieve even greater heights with our solutions. The findings of the recent Forrester Wave: Data Management for Analytics, Q1 2023 is a clear indication that IBM continues to be a leader in analytics, providing our customers with innovative and fully integrated solutions. [button link="https://www.ibm.com/account/reg/us-en/signup?formid=urx-52056" ]Read the report[/button]  IBM’s approach to data management for analytics Our purpose-built…

How technology can help save our water supply

A 2021 United Nations report finds that 2.3 billion people live in water-stressed countries which, according to the World Health Organization, is expected to be exacerbated in some regions due to climate change and population growth. To sustain lives on Earth, we must protect the health of its water resources and be efficient in our consumption, including minimizing waste in water distribution. These tasks involve a variety of equipment, assets, and people, and at IBM, we have deep experience in…

Web3 oracle nodes: The capabilities and challenges of an industry disruptor

In Greek mythology, oracles took once unattainable information from the gods and shared it with the world. Today, blockchain oracles pass information from one source to another. By design, a blockchain does not communicate with outside data sources; they only store historical on-chain user data. A blockchain oracle is the middleware that allows a blockchain to communicate with off-chain data. The addition of off-chain data provided by blockchain oracles was a huge step forward for the Web3 industry, enabling new use…