Today’s CEOs must be on the decision-making frontline when it comes to imagining and implementing Generative AI for business success

The strategic opportunities presented by Generative AI require CEOs to dive deep into their organizations’ technology agenda. For many CEOs, that means becoming tech-savvy enough to detect how Generative AI could redefine their business models, including understanding disruptions to their industries, identifying the competitive advantage of AI adoption, and understanding where this advantage could likely erode the fastest.

Given the types of Generative AI choices and their outsized impact, CEOs should dive into key decisions they would normally delegate. They must decide whether to be a first mover or fast follower, whether AI is needed for innovation or productivity, and whether they should be building or buying AI capabilities.

Yesterday’s white-hot innovations can become today’s headaches. Take multicloud for example. Many enterprises rushed into piecemeal cloud agreements without establishing a central decision-making hub, and later found themselves with technical sprawl that desperately needed streamlining. Without caution, Generative AI adoption could take the exact same path.

As more players roll out AI options, CEOs should learn from the lessons of the past and take time upfront to make key decisions, such as:

• Should we focus our investments on a few key choices, or should we maximize optionality while the competitive market for Generative AI plays out?
• How can our organization build flexibility in our execution approach?
• How will we measure direct and indirect cost and performance implications?
• How do we embed trust and guardrails in the AI model development?

In the context of Generative AI, CEOs must apply their experiences as dealmakers, venture capitalists who bet on winning strategies, and champions of business priorities to three important areas: securing computing power, selecting an ecosystem for their large language models (LLMs), and establishing centers of excellence.

The value of Generative AI hinges upon the data it consumes. This presents a problem for CEOs, as most LLMs available are not built with out-of-the-box domain, industry, or organization-level specificity. Private LLMs can deliver clear advantages in choice, cost, and control, while enabling enterprises to retain their intellectual property. To capture value and scale, enterprises need to select the LLMs and broader AI ecosystems that suit their specific needs.

CEOs can view their organization’s data as a bargaining chip. This untapped data trove could be highly valuable to companies building AI products. CEOs can consider valuing current and future-state data assets as potential inputs to new models, as long as they concurrently secure or anonymize data to avoid trust and regulatory concerns.

As with securing hardware, the CEO need not delve too deep into the technical specifics of different AI models. Instead, the CEO must calibrate the company’s AI ambition and determine whether it will be a a first mover in building custom LLMs or buy them later. Adopting a venture-capitalist-like mindset, the CEO can leverage understanding of the marketplace and established relationships with major players to determine which bets can be made safely, while considering their broader portfolio and being thoughtful about every round of investment.

A recent Deloitte and Fortune CEO survey found 80% of organizations are already implementing or likely to implement Generative AI to accelerate innovation, while 96% are doing so to increase efficiencies. To reap these expected benefits, organizations are establishing AI centers of excellence (COEs). These hubs serve as catalysts for innovation, enabling organizations to conceptualize, develop, and deploy AI solutions at scale. A COE can bring together a cross-functional group of AI experts and stakeholders to focus organizational efforts and create a consistent approach to governance and guardrails (e.g., by hiring ethicists).

The CEO’s role in implementing a center of excellence is to champion establishment and provide support and resources to facilitate inception. This includes ensuring critical elements such as hardware, data needs, and governance are sufficiently funded.

The CEO also must engage in winning hearts and minds of all stakeholders, including customers, employees, the board, and society at large. Working with their chief legal or risk officer, CEOs can help ensure that all members of the enterprise feel prepared for what’s on the horizon.

Many employees are fearful of AI transformation and are eager to understand what future jobs and skills may look like. CEOs should foster a culture of AI fluency and innovation and champion a clear purpose for AI adoption, as a matter of supercharging humans (not replacing them).

By leveraging AI centers of excellence as platforms for knowledge exchange and collaboration, CEOs can position their organizations as frontrunners in the race to Generative AI advantage.

The AI revolution is bound to alter CEO roles for the years to come. Already, CEOs have to be more tech-savvy than ever, given how important technology is to competitive advantage and ways of working. As AI becomes even more embedded into knowledge work, the details of AI adoption are expanding out of the tech leader’s domain to become CEO priorities.

This is especially true when AI adoption is still nascent. CEOs can bring their experience to bear on the many macro and micro decisions that will need to be made when a technology is both very new and very impactful. As we continue our series on leading an AI-fueled organization, we’ll delve into more aspects of the CEO’s role in preparing their organizations to pivot to the Generative AI future.