For companies, investing in artificial intelligence may equip them with genuinely novel capabilities—but those capabilities and the value they provide could vanish in an instant.
The introduction of ChatGPT in late 2022, followed by other AI tools, has brought about transformative possibilities in the business world. These generative AI platforms, such as Google’s Gemini, Anthropic’s Claude, Meta’s Llama and Perplexity AI, are rapidly evolving in both capability and efficiency. This evolution has created new opportunities for organizations to leverage these technologies as foundational tools—which can be collectively termed “public AI platforms.”
These platforms are not only advancing at a breakneck pace but are also becoming essential components in business operations. Many companies are scrambling to incorporate them into various functions, such as enhanced customer support through AI-driven chatbots, real-time document analysis for sales and legal teams and content generation for marketing departments. In short, tasks once thought too complex or resource-intensive are now within reach for firms of all sizes.
However, amid the excitement, there lies a significant challenge: The economics of AI tools are far from settled. AI platforms are controlled by for-profit corporations, and each is vying for dominance in a new, rapidly developing market. This competition has resulted in uncertain pricing structures and fluctuating service terms. Today’s pricing may be artificially low, but the next iteration of an AI tool could either offer dramatic improvements or render previous versions obsolete. These shifting variables create complexity for companies that are making substantial investments in AI capabilities.
New Business Opportunities, New Risks
At this moment in time, organizations have unprecedented opportunities to harness AI to gain competitive advantages. However, AI tools come with substantial risks, particularly given the volatile nature of the market. Companies must balance the immediate benefits of adopting AI with the potential risks posed by rapidly evolving platforms.
For corporate boards, this presents an array of crucial questions:
How should AI investments be capitalized? Historically, software and hardware investments were expected to provide value over several years with minimal updates. AI, however, is advancing so quickly that the lifespan of a tool might be measured in months rather than years.
What is the actual useful life of AI investments? Is it reasonable to expect AI tools to remain effective for 18 months, or should companies anticipate turnover in as little as three months? These are questions that need to be answered to ensure accurate financial planning.
How should companies manage obsolescence? If an AI capability becomes outdated or discontinued halfway through its expected useful life, how can organizations handle the remaining amortized value? Planning for this is critical to avoid financial disruptions.
What happens if a key feature disappears without warning? Regulatory issues or legal challenges could lead to the sudden removal of capabilities from an AI platform, posing risks for any business dependent on those features. Companies must prepare contingency plans.
Can you pivot if an AI platform stops delivering the required functionality? A key part of risk management involves having a backup plan if the AI platform a company relies on stops delivering results. The capacity to switch back to traditional methods or migrate to a different AI tool is essential.
Governance And Long-Term Strategy
Corporate governance plays a crucial role in navigating these uncertainties. As AI becomes a central part of business operations, boards must provide oversight and guidance to ensure long-term organizational resilience. This requires institutional awareness. Boards need to ensure that their AI investments are governed in a way that enables the development of organizational memory.
Boards should focus on the following areas:
AI investment governance: Boards should establish clear guidelines for evaluating and approving AI projects, particularly those with long-term capital implications.
Continual reassessment: In light of the market and technology evolving, organizations need dynamic governance structures that allow for continuous re-evaluation of investments.
Project classification: Boards and executives should work together to classify AI projects in a way that distinguishes between short-term, tactical solutions and long-term strategic investments.
The Board’s Role: Timeless Expertise In A Rapidly-Changing World
While AI’s technical complexities can be daunting, board members don’t need to become technologists overnight. The enduring principles of governance—oversight, risk management and long-term strategy—remain as relevant as ever in this new landscape. By focusing on these areas, boards can ensure they are providing value, even as the underlying technology continues to change.
In conclusion, generative AI platforms represent an exciting new chapter in technological progress. Yet, the hype must be balanced with careful governance and thoughtful investment strategies. Boards can help their organizations make the most of AI’s potential while safeguarding shareholder value against the risks of premature investment. With the right approach, AI investments can unlock significant returns for companies while minimizing their exposure to unforeseen disruptions.
Founder and CEO – The CAP Group
