Hop on to IBM Cloud Pak for Data: A jumpstart through AiR
The AI adoption journey to unlock data’s full potential is always a challenging, yet an important task for any enterprise. You have to address several hurdles—starting from defining the scope of your data strategy to bringing about change management within the organization. Enterprises also need to select and implement a fully integrated data and AI platform that can help you infuse AI through the enterprise.
Before customers make the decision to select, move or modernize an enterprise data and AI platform, they want to see a minimum viable product (MVP) that helps address their requirements and demonstrates quantifiable business benefits. Key aspects are the ability to deliver the MVP quickly, and then implement and scale it to go-to-market quickly. An accelerator can help you jumpstart from an idea to a prototype—and get you started on the platform of your choice.
Journey to AI – The adoption challenges
Some of the biggest challenges that many enterprises face during the initial journey toward AI diffusion is to understand the right data attributes and how they affect AI adoption. Basic considerations include data, skills, platform and privacy, with each bringing a unique challenge during the adoption journey:
- Data challenge: To train the AI models to derive more accurate insights, enterprises must select the right data attributes and use substantial high-quality training data in order to yield desired results.
- Skill challenge: Data scientists play a pivotal role in building an appropriate model to address your business objective. As you move ahead in your AI journey and start experiencing tangible benefits, the demand for building advanced AI models increases, while the availability of specialized data scientists remains the same, possibly creating a skills gap.
- Platform challenge: The effectiveness of your AI solution is dependent on the robustness and quality of your data pipeline. Most organizations have data scattered across environments. Integrating such data requires variety of technologies, which adds complexity to your existing enterprise IT landscape. Moreover, selecting the right AI platform to address these challenges while delivering the desired outcome for your enterprise is a key point for leadership consideration.
- Data privacy challenge: With data privacy and regulatory guidelines varying across geographies, enterprises are hesitant to upload data on a public cloud environment for retraining and testing models. This might bring in the need for additional data estate while dealing with private and confidential information.
To overcome the barrier for AI adoption in an ever-changing technology paradigm, it’s critical to have the right technology platform that provides a seamless experience of information architecture to fuel into AI. Your robust information architecture should handle the data and privacy concerns, while the unified platform can help make your AI solution scalable and reliable.
As the ecosystem evolves around robust information architecture, it becomes imperative to have a pre-built catalogue of AI models and solutions that have cross-function and cross-industry applicability. This helps lay the foundation for quicker assimilation of thoughts, and ultimately, faster adoption of the AI in your enterprise. This catalogue of solutions and accelerators not only substantially eases the development of AI solution and aids faster adoption of the platform, but also opens new ways for your commercial engagements with and within the enterprises. The pre-built, robust AI models have the potential to be productized by eliminating the privacy barriers, which helps to create opportunities for new revenue. Standardized AI models provide detailed explanations on data, model selection and how to best get the desired outcomes with the pre-built solutions, making them applicable for wider scenarios.
The way forward
Tata Consultancy Services (TCS) and IBM believe that the efficient adoption and diffusion of AI in your enterprise requires an integrated platform with industry leading information architecture products and robust AI framework. IBM Cloud Pak for Data undoubtedly helps to address this situation.
To expedite the decision making and to facilitate faster adoption, TCS has created an AI jumpstart called AI Repository (AiR) for IBM Cloud Pak for Data, that contains AI solutions such as algorithms and models for a range of industries and functions. This also acts as a starting point as well as a single stop for data scientists and AI developers to solve their specific industry problems. When beginning your AI Journey on IBM Cloud Pak for Data, AiR helps accelerate development of AI solutions, validate concepts quickly and reproduce AI models—while also providing the flexibility and extensibility to use the right algorithms.
By adopting the jumpstart like AiR, your enterprise can easily hop on to IBM Cloud Pak for Data and make smarter and better decisions by taking advantage of the TCS and IBM partnership.
→ Learn more about how TCS and IBM address the unique needs of global customers.