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Report Title
Where’s the Value in AI? (PDF version here) — BCG
Published
October 24, 2024
Most Useful For
C-suite, CTOs and CIOs, and innovation leaders.
Data Sources
Primary data comes from BCG’s 2024 Build for the Future survey of 1,000 CxOs and senior executives from 59 countries and 20 industry sectors.
Key Points
- While the vast majority — 98 percent — of companies surveyed have been experimenting with AI, only 26 percent have gone past experimentation to extract solid value from the technology. These companies, which BCG calls AI leaders, have seen 50 percent greater revenue growth than the overall average and 60 percent higher total shareholder returns over three years. These AI leader companies also have seen nearly twice the patents issued.
- The two biggest challenges related to AI, BCG’s survey found, pertained to people and processes. The top challenge: difficulty establishing ROI for the opportunities identified. The second biggest challenge: difficulty prioritizing AI opportunities relative to other business concerns.
- AI isn’t just for cutting costs and paperwork. AI leader companies aren’t only deploying AI for support functions like IT, legal, and HR. They also use AI in core business functions like operations and R&D, where they’re finding 62 percent of the technology’s added value. They’re also more likely to use the technology to generate new revenue, not just cut costs, than businesses overall, setting expectations higher for both revenue growth and cost cuts.
- Successfully harnessing AI means being thoughtful about where to use the technology, not exploring every possibility. AI leader companies pursue only about half as many opportunities as less-advanced businesses polled, but they successfully scale twice as many, and expect more than double the return on investment compared to other organizations.
- Building processes, employee roles, and strategies around AI is at least as critical as picking the right technology stack. BCG found AI leaders tend to focus about 70 percent of their resources on people and processes, 20 percent on technology and data, and 10 percent on algorithms and recommends other companies do roughly the same.
- The best places to apply AI can vary based on what your company does. While some industries like software, media, fintech, and insurance are deriving the bulk of the value from AI investments in core functions, other industries like utilities, oil and gas, and chemicals are seeing more return from applying AI in support functions.
AI leader companies pursue only about half as many opportunities as less-advanced businesses polled, but they successfully scale twice as many…
One Great Chart
How to Apply These Insights
Decide Carefully How To Use AI: While experiments can be helpful in understanding the technology, it’s ultimately helpful to take a step back and decide on a few places where AI can best be applied in your organization, then focus your resources on those. Don’t overlook potential applications in your core operations, as well as support functions.
Don’t Forget The Humans: Choosing the right AI models and providers and making sure they have secure access to your data is important. But so is building processes and organizational structures that let your team members use AI efficiently and support them as they adapt to the new technology.
Aim High: Companies successfully deploying AI set high goals for cutting costs and revenue growth and invest money, people, and other resources into deploying the technology. And they continue to see return on investment as they build AI into projects and processes of greater sophistication.
Questions to Discuss with Your Team
- What areas of our business should we focus on as we deploy AI?
- How can we best empower our people to benefit from AI?
- Where are peer companies in our industry finding success with AI?
- In what concrete ways can AI help us deliver new revenue or cut our costs?
- What are some KPIs and realistic targets for what we can achieve with AI?
