RESHAPING BUSINESS
WITH ARTIFICIAL INTELLIGENCE
By:
SAM RANSBOTHAM, DAVID KIRON, PHILIPP GERBERT, AND MARTIN REEVES
Disruption from artificial
intelligence (AI) is here, but many company leaders aren’t sure what to expect from
AI or how it fits into their business model. Yet with change coming at
breakneck speed, the time to identify your company’s AI strategy is now. MIT
Sloan Management Review has partnered with The Boston Consulting Group to
provide baseline information on the strategies used by companies leading in AI,
the prospects for its growth, and the steps executives need to take to develop
a strategy for their business.
EXECUTIVE SUMMARY
Expectations for artificial intelligence (AI) are
sky-high, but what are businesses actually doing now? The goal of this report
is to present a realistic baseline that allows companies to compare their AI
ambitions and efforts. Building on data rather than conjecture, the research is
based on a global survey of more than 3,000 executives, managers, and analysts
across industries and in-depth interviews with more than 30 technology experts
and executives. (See “About the Research.”)
The gap between ambition and execution is large at
most companies. Three-quarters of executives believe AI will enable their
companies to move into new businesses. Almost 85% believe AI will allow their
companies to obtain or sustain a competitive advantage. But only about one in
five companies has incorporated AI in some offerings or processes. Only one in
20 companies has extensively incorporated AI in offerings or processes. Less
than 39% of all companies have an AI strategy in place. The largest companies —
those with at least 100,000 employees — are the most likely to have an AI
strategy, but only half have one.
Our research reveals large gaps between today’s
leaders — companies that already understand and have adopted AI — and laggards.
One sizeable difference is their approach to data. AI algorithms are not
natively “intelligent.” They learn inductively by analyzing data. While most
leaders are investing in AI talent and have built robust information
infrastructures, other companies lack analytics expertise and easy access to
their data. Our research surfaced several misunderstandings about the resources
needed to train AI. The leaders not only have a much deeper appreciation about
what’s required to produce AI than laggards, they are also more likely to have
senior leadership support and have developed a business case for AI
initiatives.
The research and analysis for this report was
conducted under the direction of the authors as part of an MIT Sloan Management
Review research initiative in collaboration with and sponsored by The Boston
Consulting Group.
AI has implications for management and organizational
practices. While there are already multiple models for organizing for AI,
organizational flexibility is a centerpiece of all of them. For large
companies, the culture change required to implement AI will be daunting,
according to several executives with whom we spoke.
Our survey respondents and interviewees are more
sanguine than conventional wisdom on job loss. Most managers we surveyed do not
expect that AI will lead to staff reductions at their organization within the
next five years. Rather, they hope that AI will take over some of their more
boring and unpleasant current tasks.
Company becomes big by finding a successful business
model — and then scaling it massively. This necessitates building a finely
tuned system with highly standardized processes. To get promoted in such an
environment requires an almost singular focus on execution. In other words, it
requires action more than thinking. However, once executives are promoted to a
senior level, these new business leaders must be able to think strategically.
Ironically, the very skills in execution that led to their promotions often
make these executives ill-equipped for their new roles, since their strategy
thinking muscles have withered from disuse.
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