It is widely believed that AI is critical to organizational success, and has the ability to transform companies and industries. In the 2020 Deloitte “State of AI in the Enterprise” survey of executives in global firms that have adopted AI, 73% reported that AI was “very” or “critically” important to their business today, and 90% of the most aggressive adopters felt that way. More than half of the respondents’ organizations are spending $20M or more in AI-related technology and talent. And 75% of respondents expect that AI will transform their organizations over the next three years, with 61% believing that AI will transform their industries.
Transformative, critically important resources are by definition strategic for organizations, and should be, at least in part, the focus of involvement by Chief Strategy Officers (CSOs) as to how they will be used in the business. Therefore, it’s not too difficult to argue that CSOs should be involved in AI, assisting in if not driving decisions about priorities for AI use cases and implications for products, processes and relationships within the company.
Some organizations, including “digital native” firms like Alphabet/Google, and more traditional businesses like the health insurer Anthem, are striving to be “AI first.” They don’t necessarily believe that AI can solve all their business problems, but they turn to AI first when addressing how technology can impact their businesses. For an organization to portray itself as “AI first” and not to relate AI initiatives to strategy simply doesn’t make sense.
Two Connections Between AI and Strategy
There are two major ways in which AI and strategy should be connected, each of which can benefit from CSO involvement. There is, as suggested above, the issue of how AI affects or enables business strategy. If it can improve products and services, transform channels to customers, optimize supply chains, and so forth, it should be part of a company’s strategic deliberations.
The second strategic focus with AI is to develop a strategy for AI itself. There are many key decisions to be made about how a company uses and manages AI, including how it builds or buys AI capability, where it sources key talent, what projects it takes on, and how AI initiatives relate to digital platforms and processes.
We see no reason why CSOs shouldn’t be involved in both. They can bring expertise on the strategic process, knowledge of other strategic directions in the business, and valuable relationships with business and functional leaders and general managers.
The CSO and the Role of AI in Corporate Strategy
Chief Strategy Officers who see the importance of AI and want to embed it into their corporate strategies face several key issues. They include:
• Educating senior managers on AI—In order for a strategy process to incorporate AI, senior managers who participate in strategic planning need some familiarity with the different AI technologies and use cases for which they are appropriate. Strategy is a “matching” process of business initiatives and AI capabilities, and participants need an awareness of both. CSOs may want to sponsor formal or informal education initiatives to ensure broad engagement and participation in the AI-related aspects of business strategy.
• Within the strategic process, the enabling effect of AI and other technologies needs to be incorporated into consideration of strategic alternatives. This may require changes to the methodology for strategic planning. What could we accomplish in our marketing programs, for example, if we had better predictions of customer behavior using machine learning? How could we transform customer service with a conversational agent? There can’t be AI-rich strategic initiatives without an ideation process that includes AI capabilities. Similar thinking could be applied to other technologies such as blockchain, cloud, and mobile.
• Beyond ideation, AI will only be embedded into a company’s products and processes if it actually builds or buys the systems that do AI tasks. Creating linkages between a strategy and the AI development/deployment cycle is critical for getting strategic AI systems in place. The CSO will need influence into prioritization of AI projects and should have the ability to monitor AI project progress.
The CSO and a Company’s AI Strategy
CSOs are well-suited to participate in the development of AI strategy if they know something about the major types of AI and how they are used in business. They almost definitely meet other participation criteria, including being effective at communicating to managers in non-technical terms, understanding the key issues of the business and its current strategic direction, and possessing facilitation and process skills.
Some of the components of an AI strategy in which a CSO can participate include:
Determination of objectives—One key issue in an AI strategy is to what objectives to apply the technology. A Deloitte listing of objectives (with respondent percentages from 2018) from AI in a recent survey includes:
• Enhance the features, functions, and/or performance of our products (19% ranked first, 51% among top three)
• Make better decisions (14% and 35%)
• Optimize internal business operations (12% and 36%)
• Create new products (12% and 32%)
• Free up workers to be more creative by automating tasks ((10% and 36%)
• Pursue new markets (8% and 25%)
• Capture and apply scarce knowledge where needed (8% and 25%)
• Optimize customer processes like marketing and sales (7% and 30%)
• Reduce headcount through automation (7% and 22%).
CSOs should be well positioned to know which business objectives are the most valuable ones for the application of AI. There may be sub-objectives to select among; which product or service, for example, is most worthy of being improved by AI?
What data to employ?—A major part of AI involves analyzing and extracting insights from data. An important strategic component is to determine what type of data the company will be using in its AI projects, and how that data might confer competitive advantage. Ideally a company would have some proprietary or exclusive data that it could use in its own products and processes. Companies are also increasingly using external data in their analytical and AI models.
What technologies to adopt—What AI technologies should an organization acquire or develop in order to meet its objectives? That is a complicated question that is important for organizations to answer. AI is not one technology, but a collection of them—including statistical machine learning, neural networks, natural language processing and generation, robotic process automation, and so on. Even previous AI technologies like rule engines can still be useful for some applications. Beyond the choice of technologies, companies need to decide whether to build or buy the technology capabilities, whether to use proprietary or open source software, whether to use a single vendor’s tools or employ “best of breed,” whether to use a broad “platform” or single applications, and so on. All of these issues need to be addressed in an AI technology strategy.
Where to source AI talent?—A key question for any organization pursuing AI initiatives is where to source people who can do such work. Shortages of AI-qualified data scientists and developers are well-known, although there are increasing numbers of university graduates with data science and AI skills. The choices for talent strategy are similar to those for AI technologies: they can be bought (hired), built (trained) or rented (from consultants or vendors). Talent strategies should also address what happens to employees whose work is automated by AI, and how reskilling and upskilling for people in redesigned jobs will be accomplished.
There may be other components of AI strategy, but these are the most common ones. CSOs may even be able to advise AI experts on what aspects of AI strategy would be most helpful to the organization. They can also help to relate AI strategy to the organization’s overall digital strategy.
There is little downside, and much potential upside, to involving Chief Strategy Officers in a company’s deliberations about AI. The technology is significant enough that they should not wait to be asked, but should take the initiative to learn about AI and become an integral part of strategic decision-making about it.