Board Members Should Recognize the Significance of Artificial Intelligence

Board Members Should Recognize the Significance of Artificial Intelligence

AI isn't about replacing humans, it's about boosting human abilities, as Sundar Pichai, Google's CEO, put it. With artificial intelligence (AI) significantly disrupting the strategic, operational, and competitive landscapes, boards have a responsibility to guide this transformative change for the benefit of shareholders.

Boards are becoming aware of AI's pivotal role in a company's future. Discussions often revolve around generative AI's potential for content creation and code generation. However, concerns about AI-related risks, such as employees using generative AI to upload confidential material, and the rapid pace of AI development, remain prominent. As the guardians of enterprise risk management, boards must ready themselves for AI's potential pitfalls.

One significant risk crops up when employees use AI tools unsupervised, especially when these tools haven't been tested at scale. For instance, junior lawyers may use AI for research, resulting in fabricated reference cases. Furthermore, AI introduces significant privacy, security, and regulatory risks. "Prompt injections," where hackers manipulate generative AI to trigger security attacks, are a recent threat. Users also face legal risks from inadvertently using copyrighted material, due to unclear AI training methods.

Though the legal framework around AI is still developing, watermarking techniques are emerging, and some major tech companies offer user indemnification. Despite these advancements, the law remains vague, potentially leading to cease and desist orders for users of generated content. As the discussion on broader AI risks unfolds, boards must stay vigilant.

On the flip side, AI presents significant strategic opportunities, offering new efficiencies and enabling mass personalization in marketing, customer service, and product offerings. It can also dramatically improve predictions for operational efficiency, such as predictive maintenance and supply-chain management. AI will redefine competition as leaders reshape their value propositions, cost structures, and differentiation strategies. Boards must verify that operations align with strategy and meet shareholder expectations, as AI disrupts competition, value propositions, operations, and economic models. Consequently, boards must reconsider these aspects, challenging management with fundamental questions about the company's strategic direction in an AI-driven world.

Leading boards are concentrating on five principal strategies to navigate the AI landscape:

1. Prioritize Data as Core Asset: First-party customer data is invaluable for prioritizing customers, identifying triggers for follow-up, and personalizing interactions. Richer AI models are built by integrating and capturing more customer information across the enterprise and generating new data through innovation. Boards want in-depth analyses of data management processes, urging management to adapt business models to collect and utilize data more efficiently.
2. AI Strategy, Implementation, and Risk at Board Level: AI influences strategy, competitive positioning, investment, ethics, bias, and talent. Regular AI strategy discussions are taking place, and specific oversight is being delegated to committees like audit committees for enterprise risk and technology committees for tools. CEOs are expected to preside over AI handling within the C-suite, with AI implementation goals integrated into their annual objectives to ensure accountability.
3. Workforce Strategy and Talent Needs: With AI's potential to alter traditional workforce models, there will be a demand shift for roles such as a lower demand for product managers and an increased need for data engineering and data science talent. Boards engage with leadership on AI-related skills, reskilling existing workforces, talent sourcing, and adopting AI ethics, privacy, and security policies. The growing supply-demand gap for AI talent is prompting talent and compensation committees to address this issue proactively.
4. Shape the Industry Ecosystem: AI's integration raises strategic questions about what to build versus what to buy or access through APIs, such as software, algorithms, data, and customer experience partnerships. Most companies will rely on large tech vendors for chips, systems capacity, access to scaled training data, and AI development talent. Specialized applications, like content generation and optimization models, will come from a mix of off-the-shelf solutions, custom developers, and in-house teams. Boards demand guardrails, such as protecting employees' data from other companies' models and ensuring first-party data remains private. Alignment with regulatory guidelines, privacy standards, security, transparency on training sources, and regular bias assessments are also essential. Companies are experimenting with offerings from major LLM providers who offer an openly trained foundation that can be further optimized, offering partitioned instances of models to protect uploaded company data. Boards are realizing these are just a few of many conditions to consider.
5. Seek Transformative and Measurable Impact: While initial AI implementations focus on incremental efficiency improvements, boards can push for larger impacts, including reshaping value propositions, accelerating innovation, improving yield management and pricing, boosting customer acquisition, and enhancing predictive maintenance and staffing. Boards approve new budgeting strategies, such as creating cross-business pools for forward-moving AI investments (e.g., integrating new sensors, building large cloud bases for data, and establishing innovation funds) to provide flexibility for these initiatives. AI remains a standing agenda item for board meetings, with discussions focusing on speed of implementation and progress monitoring.

In conclusion, boards have a duty to protect shareholder interests. Given AI's fundamentally disruptive nature strategically, operationally, and competitively, boards must lead and oversee this transformation to ensure a company's continued relevance. Every board member must familiarize themselves with AI to effectively manage the risks and opportunities it presents.

References:

[1] Stickdorn, M., & Schweitzer, J. (2020). This Is Service Design Doing: Applying Service Design Thinking in the Real World. O'Reilly Media, Inc.

[2] Teehan, P., & Raskas, P. M. (2016). On the Intersection of Design and Artificial Intelligence (AI). Smashing Magazine.

[3] Wang, M. (2022). AI Reality Check: Addressing Artificial Intelligence's Growing Pains. Harvard Business Review.

[4] Edelman, D., & Sharma, V. (2023). It's Time for Boards to Take AI Seriously. Harvard Business Review.

[5] Topitzes, J. (2019). Your Company's Digital Transformation Checklist. Harvard Business Review.

Boards are examining the strategic implications of artificial intelligence (AI) integration, recognizing that AI tools can provide mass personalization in marketing, customer service, and product offerings, as well as improve predictions for operational efficiency. However, they are also mindful of AI-related risks, such as potential misuse of AI tools for uploading confidential material and the emergence of privacy, security, and regulatory threats.

To navigate the AI landscape, leading boards focus on prioritizing data as a core asset, implementing AI strategies at the board level, shaping the industry ecosystem, addressing workforce strategy and talent needs, and seeking transformative and measurable impact. By understanding AI's potential pitfalls and opportunities, boards can lead and oversee this transformation to ensure a company's continued relevance and protect shareholder interests.

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