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Winning With AI: Pioneers Combine Strategy, Organisational Behaviour, and Technology

Artificial Intelligence

Sam Ransbotham, professor in the information systems department at the Carroll School of Business at Boston College, Shervin Khodabandeh, senior partner and managing director at BCG, Ronny Fehling, partner and associate director at BCG, Burt LaFountain, partner and managing director at BCG and David Kiron, executive editor of MIT Sloan Management Review summarise the findings from a two-phase research effort between MIT Sloan Management Review and Boston Consulting Group.

After several decades of progress, AI technology is now poised to become a significant source of value for a wide range of businesses. In the 2019 MIT Sloan Management Review and Boston Consulting Group (BCG) Artificial Intelligence Global Executive Study and Research Report, nine out of ten respondents agree that AI represents a business opportunity for their company.

In addition, a growing number of leaders view AI as not just an opportunity but also a strategic risk:
“What if competitors, particularly unencumbered new entrants, figure out AI before we do?” In 2019, 45 per cent perceived some risk from AI, up from an already substantial 37 per cent in 2017. This shift suggests an increasing awareness of and concern with competitors’ use of AI. In China, perceived risk from AI is even higher.

Significant challenges remain, however. Many AI initiatives fail. Seven out of ten companies surveyed report minimal or no impact from AI so far. Among the 90 per cent of companies that have made at least some investment in AI, fewer than two out of five report obtaining any business gains from AI in the past three years. This number improves to three out of five when we include companies that have made significant investments in AI. Even so, this means 40 per cent of organisations making significant investments in AI do not report business gains from AI. The crux is that while some companies have clearly figured out how to be successful, most companies have a hard time generating value with AI. As a result, many executives find themselves facing a set of AI realities: AI is a source of untapped opportunity, it is an existential risk, and it is difficult.

Above all, it is an urgent issue to address. How can executives exploit the opportunities, manage the risks, and minimise the difficulties associated with AI? How should they navigate all three factors?
Our findings — based on a survey of more than 2,500 executives and 17 interviews with leading
experts — provide a data-driven view of what organisations that succeed with AI are doing and what
real success with AI looks like. Companies that capture value from their AI activities exhibit a distinct set of organisational behaviours. They:
• Integrate their AI strategies with their overall business strategy
• Take on large, often risky AI efforts that prioritise revenue growth over cost reduction
• Align the production of AI with the consumption of AI through thoughtful alignment of business owners, process owners, and AI expertise to ensure that they adopt AI solutions effectively and pervasively
• Unify their AI initiatives with their larger business transformation efforts
• Invest in AI talent, data, and process change in addition to (and often more so than) AI technology.

They recognise AI is not all about technology.
The net effects of these behaviours, and their underlying commitments, are to address difficulties
generating value with AI, manage unavoidable competitive and implementation risks from AI, and
effectively exploit AI-related opportunities
Addressing difficulties
To a large extent, difficulties with generating value from AI show up in the data as organisational rather than technological. Companies that focus solely on the production of AI (data, technology, tools) are less likely to derive value than those companies that actively align business owners, process owners, and AI owners. Leaders enable their organisations to consume AI as much as to produce AI.

AI efforts led by C-level executives and closely co-ordinated with the company’s broader digital transformation are more likely to generate value than those that are led by other executives or unintegrated with digital transformation. Companies that treat AI as a ‘technology thing’ struggle to deliver value: An IT focus on AI tends to generate less value than a broad strategic focus.

Those companies that obtain business value from AI build internal teams and rely less on outside vendors; they selectively import experienced AI talent for technical leadership roles; and they upskill their existing workforce to enable AI literacy and understanding of how to manage with AI. Despite talent scarcity, companies of all sizes across industries report similarly positive outcomes when they make these three talent investments.

Managing risks
Our research surfaced two broad ways that companies are managing risks that emerge either directly or indirectly from their and others’ AI deployments.
First, companies that have obtained value from AI are more likely to manage proactively: They make
bigger, sometimes riskier, investments. These are not gambles, however, but rather, calculated strategy.

Second, in fast-moving market environments, strategic alignment becomes more challenging and
more critical to get right. Misalignment, accordingly, becomes a greater and more common risk.
Successful leaders pay attention to AI as one tool in a broader strategic context; this, combined
with a focus on organisational ability to consume AI, mitigates the risk of strategic misalignment. Some interviewees describe reinforcing alignment benefits once AI is successfully at work, pointing to successful AI applications that produce integrated customer perspectives, new metrics, and cross-functional behaviours that enable work to be done more effectively.

Exploiting opportunities
Companies that derive value from AI are more likely to integrate their AI strategy with their overall corporate strategy. Organisations that are most effective at obtaining value from AI more likely generate value from AI-driven revenue, rather than from cost savings alone. Most executives believe that the highest future value from AI will be on the revenue and growth side rather than on the cost side.

Genuine success with AI — over time — depends on generating revenue, reimagining organisational
alignment, and investing in the organisation’s ability to actually use AI across the enterprise. None of this is easy to achieve. It is clear, however, that a growing number of executives have determined that finding the right approach to AI is in their company’s best interests.

Capitalising on an AI-enabled strategy
The report began by noting a growing sense of urgency surrounding the adoption of AI in businesses.
Sebastian DiGrande at Gap Inc. calls it “an existential threat: If we do not change the way we operate, the tools we use, the degree of automation and AI that we leverage, the industry and the customer will move on without us. And the degree of fixed cost and the narrowness of the margin structure in an industry like retail means that that can make all the difference between winners and losers, between the survivors and those who fall out.”

Under pressure from competitors, and with so many targets of opportunity, executives face numerous hard choices and trade-offs. These are the essence of strategy. AI can be revolutionary, but executives must act strategically. Acting strategically means deciding what not to do.

We saw more examples this year of companies aspiring to use AI across the enterprise. Consider the
technology-transformed future envisioned by Philips Healthcare. This is a company that excels in several separate domains today — MRI machines, CT scanners, ultrasound, and digital pathology — but Tas insists that ‘if you buy in on the concept’ that the company could provide patients with ‘precision diagnosis’ and ‘connective care,’ the obvious challenge is ‘how to create synergies between those businesses; you’re forced to look beyond the boundaries of each of the businesses’. AI projects that focus on targeted solutions create a positive pressure for organisational integration on two levels: by forcing a level of data hygiene that yields greater integration across functions, and by revealing exciting opportunities for innovation that organisations can only realise if many disparate parts of the organisation pull together.

In sum, the leaders not only anchor their applications of AI in their fundamental business strategy, they approach the use of AI as an organisational initiative, in which data and technology are foundational, but organisational behaviours and ways of working make the difference in generating business value.

These principles, however, do not constitute a formula or a step-by-step guide to extracting value from AI. Business leaders who seek value from AI still need to make choices and trade-offs as they navigate the path from their current state to where they aspire to be. One such choice might be focusing on AI projects with more certain, near-term impact rather than larger, riskier projects whose effects will be felt in the longer term. Another choice might be between building and scaling internal teams quickly versus starting initially with a critical mass and scaling slowly.

Executives need to execute strategy with AI in their own context and from their own starting point. So while the survey data shows that pioneers tend to embrace larger, riskier initiatives focused on revenue growth, this does not imply that taking on such initiatives is the right ‘first move’ for any company seeking value from AI. Taking on a lower-risk cost reduction initiative is less likely to produce transformational strategic results and is empirically less likely to create expectation of increased value over time. Doing so, however, can allow a company to develop new ways of working across the business in order to start building organisational capabilities to get value from AI.

A caution: Most AI success stories focus on improving existing business processes, whether in
sales, marketing, pricing, servicing, forecasting, manufacturing, or the like. But these improvements
are comparable to improving the gas mileage of combustion engine vehicles in an era of new transportation possibilities. Business executives need to consider how they can reinvent and reimagine many of those processes in the context of what AI enables.

This is where AI’s true potential will emerge: not in doing the same thing better, faster, and cheaper but by doing new things altogether. This is where AI will disrupt industries the most.
As business leaders look to the future, they must also carefully consider how AI may affect their talent strategy. In most companies, the skill sets and success profiles of the workforce (and the talent pools from which they will come) will be materially different in the next decade or two than they are today; the effect of this change on a company’s long-term HR strategy will be nothing short of massive.

One thing is certain, If AI initiatives are not core to a company’s business strategy, they are unlikely to create meaningful value and scale. Finally, if a company’s current business strategy ignores AI as a risk or as an opportunity, it probably needs revisiting.

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