Published on October 29, 2023, 8:45 pm

  • AI Implementation in Business Strategies: Key Considerations
  • The 2023 Gartner CIO and Technology Executive Survey reveals that a significant number of CIOs have implemented AI technologies, with more planning to do so. A concise AI strategy document capturing vision, benefits, risks, KPIs, and best practices is recommended. Adoption levels vary across regions in Asia, with countries like Singapore and Australia advancing in analytics while others embrace cloud technologies. While AI can automate tasks, it cannot replace humans entirely. The copilot approach is successful in generative AI projects. Starting small and gradually expanding AI usage allows organizations to understand ROI.

The 2023 Gartner CIO and Technology Executive Survey revealed that a significant number of CIOs have already implemented artificial intelligence (AI) technologies in their organizations. According to the survey, one-third of the CIOs stated that they had already deployed AI, with an additional 15% planning to do so within the next year.

However, effectively incorporating AI into business strategies requires careful consideration of factors such as its impact on business value, risk management, talent requirements, and investment priorities.

John Hillery, Managing Vice President in Peer and Practitioner Research for the Gartner CIO Research Group, recommends that CIOs develop a concise AI strategy document. This document should capture their vision for AI implementation, assess potential benefits, address any risks involved, establish key performance indicators (KPIs), and outline best practices for value creation.

Hemanta Banerjee, Vice President of Public Cloud Data Services at Rackspace Technology, believes that adoption levels vary across different regions in Asia. Countries like Singapore, Korea, and Australia have made significant advancements in analytics and AI usage. On the other hand, countries like Indonesia and Vietnam have embraced cloud technologies directly and are leveraging emerging technologies like open AI.

There are misconceptions about what AI can actually achieve. While it is a powerful tool that can automate various tasks, it cannot fully replace humans. Humans possess unique qualities such as creativity, problem-solving abilities, and empathy that are crucial in many job roles. The entertainment industry has fueled wild imaginations about what current forms of AI can accomplish; however vendors and consultants are now tempering expectations around these possibilities.

To navigate these challenges effectively, Banerjee suggests treating AI initiatives like any other intellectual property project. He emphasizes the importance of agility in teams and constantly redefining success along the way through experiments. While AI can automate processes and replace certain jobs to an extent, human judgment is still indispensable.

In the generative AI world, there are three approaches. The “copilot” approach involves AI suggesting actions for humans to decide upon. In the “autopilot” approach, AI makes certain decisions and hands them off to humans to complete. Lastly, the “autonomous” approach entails AI making all decisions without human intervention. Successful projects typically use the copilot approach.

Banerjee recommends focusing on internal use cases when starting an AI journey to minimize risks and enable iterative learning. He advises consulting with AI experts and partnering with solution providers specializing in AI to establish robust governance structures and data platforms.

To embark on an AI initiative, Banerjee suggests starting with a small product focus to demonstrate quick wins and understand the return on investment (ROI). This allows organizations to expand their usage of AI gradually.

In summary, integrating AI into business strategies requires a well-defined strategy document that addresses vision, risks, KPIs, and value creation best practices. It is important to understand that while AI can automate tasks, it cannot replace humans entirely. Organizations should approach AI initiatives with agility, treating them like any other IP project. By experimenting and iterating along the way, organizations can uncover the true value of AI for their business.


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