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As the march of AI continues, it is crucial that companies identify how to and who manages the opportunities it creates, as well as the risks it can pose.
Responsibility for AI strategy in a company is rarely restricted to a single person. This is because AI impacts everything, from supply chains and product delivery to interpreting data, identifying new products and marketing them.
AI, if used effectively, can reduce costs, labour needs and increase the speed of “go to market”. However, we all know it is a double-edged sword, with risks including misinterpreted data, not using an adequate population of base data and (un)ethical business practices.
As such, the responsibility for a company’s AI strategy must be a collaborative effort spanning the C-suite, board of directors, and specialised business unit leaders.
However, let’s be very clear – the ultimate ownership must lie with the CEO and the Board of Directors.
AI touches every aspect of business, and leaders need to fully understand the potential risks and opportunities it offers. Nearly 30% of AI-leading companies now have AI or generative AI formally on the board agenda. This reflects a growing recognition that AI isn’t a narrow IT or innovation topic; it’s a full-board issue touching risk, growth, and competitive positioning.
Top-performing enterprises have moved beyond using AI to improve existing processes. They are now focused on using AI to build new products, open new markets, and reinvent business models.
Where to Start?
The starting point for a board or CEO to consider the potential for AI in their company can come down to 2 basic questions:
- Where to deploy AI? and
- How to manage the risks that come with it?
The more effective companies have already made their choice.
In these companies, the CEO and the C-suite are setting the tone for AI. They acknowledge that AI is not a separate technical initiative but a strategic need that transcends all aspects of the business; AI strategy is a bridge spanning technical teams to the business, commercial, and operational strategies.
The leaders of respective teams, such as product offerings, customer experience, growth, and finance, whatever it may be, define their goals (much as in a traditional organisation structure), the AI lead and their team respond by making the goals achievable by best harnessing AI. This ensures that AI innovation will have an ultimate ROI focus rather than “AI for AI’s sake”. However, this only works when the CEO puts AI on the agenda and encourages the use of an internal team to enhance the business strategy with effective AI.
Final Thoughts
A strategy of “AI for AI’s sake” will not work – AI is a lever used to best achieve the ultimate business strategy. Whilst roles such as Chief AI Officer (CAIO) and Chief Data & Analytics Officer (CDAO) are growing in popularity and, indeed, need, the ultimate ownership for AI in a business must sit at the top. If a CEO or a Board delegates this responsibility, the tail (AI) will undoubtedly begin to wag the dog (strategy).
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