Strategy For and With AI, a recent article in the MIT Sloan Management Review by David Kiron and Michael Schrage, argues that while formulating a comprehensive strategy for the use of AI technologies is absolutely necessary, it’s not sufficient. “Creating strategy with AI matters as much - or even more - in terms of exploring and exploiting strategic opportunity.” The article is based on a survey of over 3,000 executives, managers and analysts from companies in over 100 countries and 20 industries, as well as on interviews with executives and academics.
AI is expected to be the biggest commercial opportunity for companies and industries over the next couple of decades. Two 2018 reports, one by PwC and one by McKinsey, estimated that AI has the potential to incrementally add around $13-$15 trillion to global economic output by 2030. The growth will come from productivity gains, - e,g, the continuing automation of routine tasks, and AI-based tools to augment human capabilities, - and from increasingly sophisticated, AI-enhanced products, services, and system-wide applications.
Machine learning advances, like deep learning, have played a central role in AI’s recent achievements, giving computers the ability to be trained by ingesting and analyzing large amounts of data instead of being explicitly programmed. Machine learning methods for solving problems, - subtle adjustments to the numerical weights that interconnect huge number of artificial neurons, - are radically different and complement the way humans solve problems. But, while being a very powerful tool, machine learning, and AI in general, lack all-important human qualities like common sense and empathy, so their decisions and suggestions should be carefully reviewed by humans. People and technology must closely collaborate, with each playing the particular role they are best at.
Every day we can read about the latest AI advances from research labs, startups and large companies. AI technologies are approaching or surpassing human levels of performance in vision, speech recognition, language translation, playing championship-level Go, and the early detection and diagnosis of various forms of cancer. But, can AI help address broad, open-ended and ambiguous problems like developing and executing a competitive business strategy?
Strategy typically involves a series of interrelated steps, including analyzing the overall business and market environment; setting one or more end goals; formulating a high level plan to achieve the end goals; and mobilizing resources to execute the plan. Experimentation and market data help to continuously redefine and reframe the problems being addressed as well as their solutions. In a well-functioning organization, the key responsibility of operational and mid-level managers is to execute business plans and deliver against their commitments.
Strategies are generally based on specific beliefs about a changing and unpredictable future. Those at the higher levels of the organization, - senior managers, executives and board members, - are responsible for managing strategic uncertainties by understanding the risks inherent in their commitments, carefully monitoring business results and market conditions, and adjusting the firm’s strategy as appropriate. These should be their top priorities, because firms can only prosper over the long term if they’re able to learn, adapt, and regularly transform themselves. Given the fast pace of technologies, markets and economies, successful firms may well need to reinvent their strategies every five to ten years.
According to Kiron and Schrage, AI can play a major role in translating technological advances into strategic advantage. AI can assist management teams in the creation of novel strategies, and help them determine which outcomes to measure, how to measure them, and how to prioritize them.
In today’s data-rich markets, top business leaders rely heavily on analytics and quantitive measures to define, communicate and drive strategy. Such a reliance plays strongly to AI’s strengths. In their research, the authors found that in an era of increasing AI investments and capabilities, enterprise strategy is defined by the key performance indicators (KPIs) that business leaders choose to optimize, which can be customer centric, cost driven, process specific or investor oriented. “These are the measures organizations use to create value, accountability, and competitive advantage. Bluntly: Leadership teams that can’t clearly identify and justify their strategic KPI portfolios have no strategy.”
The article cites the Internet as a technology that’s played a major role in transforming a company’s overall strategy. Internet-based omnichannel strategies, for example, have been used in a number of industries, - e.g., retail, financial services, healthcare, government, - to provide an integrated, seamless user experience to their customers. Internet-based platform strategies are another example which have transformed major industries, like retail, transportation and lodging.
Strategies express what company leaders seek to emphasize and prioritize over a given time frame. They articulate how and why an organization expects to succeed in its chosen market, be it a superior customer experience, increased profitability or greater market share. Organizations then create measures, like KPIs, to characterize and communicate the strategic outcomes they’re after, and to hold their managers accountable for the results. “Data-driven systems, enhanced by machine learning, convert these aspirations into computation. World-class organizations can no longer meaningfully discuss optimizing strategic KPIs without embracing machine learning (ML) capabilities.”
“In an always-on big data world, your system of measurement is your strategy. Determining the optimal ‘metrics mix’ for key enterprise stakeholders becomes an executive imperative… Our research shows that AI transforms the strategist’s choices about which KPIs to optimize and how to optimize them… For any KPI portfolio, identifying and calculating how best to weight and balance individual KPIs becomes the strategic optimization challenge… AI makes that feasible, affordable, and desirable… The true strategic opportunity and impact of these technologies is the chance to rethink and redefine how the enterprise optimizes value for itself and its customers.”
“These principles have sweeping and disruptive implications. As ‘accountable optimization’ becomes an AI-enabled business norm, there is no escaping analytically enhanced oversight. Boards of directors and members of the C-suite will have a greater fiduciary responsibility to articulate which KPIs matter most - and why - to shareholders and stakeholders alike. Transformative capabilities transform responsibilities. You are what your KPIs say you are.”
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