As CEOs consider implementing AI-driven decision-making, it is vital that they employ the services of the right digital experts and set a clear framework for its use.
Ask Chief Executive Officers (CEOs) what their most challenging issues are for the coming years and you’ll get a list that moves far beyond financial data and operational data. From sustainability to cybersecurity, diversity, equity and inclusion, CEOs are grappling with ever-increasing complexities.
As a result, they are making decisions faster than ever in a world that has moved beyond looking solely at shareholder value. Today’s boardroom is debating the ethics, feasibility and value of AI-driven decision-making versus human involvement. And it’s fair to say that many of the accounts about its alleged dangers mask a far greater story – the ways that AI can help businesses of all sizes boost competitiveness, enhance efficiencies, and deliver greater value to their customers.
It’s therefore little wonder that business leaders remain unsure about how to implement generative AI into their enterprise systems.
Starting a generative journey
First, it’s important to note that generative AI is not a new concept; the machine-learning techniques behind it have evolved over the past decade. Generative AI is a technique, backed by foundation models, which interprets and manipulates patterns in pre-existing data to generate entirely new data; including text, images, video and code. Foundation models can be fine-tuned and adapted to a wide range of tasks and operations.
Until very recently, generative AI had been difficult to scale and implement. But advances in the use of foundation models are helping to make deploying AI significantly more scalable, affordable and efficient, which is in turn helping to drive a wider awareness of its capabilities. As a result – and according to IBM’s recent ‘‘CEO decision-making in the age of AI’’ study – half of CEOs report they are already integrating generative AI into products and services, and 43% say they are using generative AI to inform strategic decisions.
Balancing boardroom pressure with skills
Pressure is starting to build in the boardroom, too, with 66% of board members and 64% of business investors encouraging acceleration in generative AI adoption. In tandem, three-quarters of CEOs believe that an organisation’s competitive advantage will depend on having the most advanced generative AI.
But this growing enthusiasm isn’t uniformly shared across organisations. While 74% of CEOs agree that their team has the knowledge and skills to incorporate generative AI, just 29% of other executives believe their organisation has the in-house talent to adopt it and only 30% say their organisation is ready to adopt AI responsibly.
To get ahead of this wave, top CEOs are initiating and deepening conversations with their teams about the use of AI – removing roadblocks to progress, implementing training strategies, and ensuring safety measures are in place to promote responsible AI.
Underpinning AI innovation with guidance
It may be tempting for enterprise leaders to see generative AI as the cure for all their business afflictions, but if a measurable ROI is to be achieved, prescriptive steps need to be taken.
This means creating rules around the use of generative AI. Without proper thought, businesses risk failing to optimise the available benefits; there may also be hazards around ethics, bias and the protection of intellectual property. Nevertheless, just one in four CEOs say they have issued any guidance on the use of generative AI within their organisation.
IBM has extensive experience in helping enterprises successfully prepare for the adoption of generative AI, identifying three important actions for CEOs to help deliver the best results:
- First, ensure that technology and data training are embedded across an enterprise, especially for those with responsibilities around business, technology and data strategy. Acquiring the right digital experts is vital.
- Second, be prepared to terminate projects that are not delivering the intended value, supporting strategic goals or following ethical guidelines. It should not be a case of simply ‘‘adding AI’’, but ‘‘starting with AI’’ to initiate the right conversations and use cases.
- Third, use a broad range of planning approaches, including forecasting and modelling, scenario-based planning, benchmarking and data mining. Collaboration is key.
Visionary CEOs generally have a positive outlook; ethically deploying AI and setting a clear framework as to how it can inform decisions up and down the line, will help to turn that vision into a reality.
About the Author
As Managing Partner, EMEA at IBM Consulting, Neil McCormack leads a team of experts to help clients across all industries drive business transformation through hybrid cloud and AI technologies. Neil has worked at IBM for almost twenty years and holds unique insight into the issues and opportunities facing the region’s business leaders and CEOs.