AI Has Moved Beyond Hype — It Is Driving Performance and Deployment Is Widespread

Artificial intelligence — or AI for short — has captured the world’s attention in recent months. It has captured the attention of business leaders as well. 

Why is AI suddenly in the spotlight? The upsurge in media coverage and boardroom conversation is thanks largely to the arrival of generative AI in early 2023. ChatGPT4, the best known example, quickly established the fastest-growing user base in tech history, according to UBS.

It’s no surprise that generative AI exploded on the scene. Its ability to generate text and graphics based on a few simple prompts makes it easy to grasp — and sparks concerns about its potential (somewhat exaggerated for now) to take the place of knowledge workers.  

But AI itself is not new — more conventional artificial intelligence systems have been at work in business settings for years, analyzing data and creating efficiencies in a host of processes. Generative AI has captured attention and helped spotlight the broad potential of all AI for executive decision-makers. It may also serve to accelerate AI investment. At the same time, there is the risk that generative AI hype overshadows other forms of AI that are already deployed and creating value in multiple functions across multiple industries.  

The central question — What is the impact of AI and what is its value in driving strategy and superior business outcomes? — is top-of-mind for leaders and organizations. What are they currently thinking about AI? How are they incorporating it into critical processes and operations? Where is it getting traction? What is its role in achieving business objectives? 

To find out, L.E.K. Consulting surveyed 1,000 executives across multiple industries. Our goal was to take a deep dive in order to more fully understand both the full range and the nuance of AI’s impact. We focused on the here-and now — the current deployment of AI and its impact on performance. We asked: How are you measuring success? Are you meeting KPI targets or not? We also asked about the farther-reaching question of what’s next.  

We questioned executives in more specific terms, asking them about the expected impact of AI — both generative and AI more broadly — on specific lines of business and on business functions. What functional areas and objectives are the focus of their AI investment? Are they using in-house AI tools or relying on third parties? 

We were able to get to the core of what is happening in the market and really dig into the impact of AI on businesses’ strategies. 

AI Has Already Established Strong Traction in Organizations 

 This is what we know, among the key takeaways: 

• AI is not “on the horizon.” It is already well established. More than half the executives reported that their companies are already using AI across a wide range of functions.

• And it is having a measurable impact on performance. Executives reported that their AI investments have led to improvements in specific KPIs — including reduced customer acquisition cost (CAC), increased lifetime value (LTV), among others. 

• “Digital progressives” expect bigger business impact. Regardless of industry or size of business, companies that have proven success with prior digital initiatives — we call them "digital progressives" — are far more likely to expect AI to have a major impact on their industry and their business processes.  The resulting imagination gap between this segment and other businesses — the "digital mainstream" — could be a major determinant of future winners and losers with respect to AI. 

• While some executives expect AI to replace jobs, more believe its primary impact will be to enhance productivity across the board. 

• AI's impact extends well beyond marketing and customer service. Hype about generative AI has focused, not surprisingly, on personalization, marketing and other forms of content generation. But in fact, AI (beyond generative AI) deployment is much more widespread — it has been deployed across a range of functions including supply chain management, planning and procurement. There is strong interest in marketing and pricing functions; however, they are a focus of testing.

• Companies plan to invest broadly in AI — and expand it across more functions. Leaders report they expect to make significant AI investments across all functional areas. They will develop in-house capabilities but also rely on third parties. Interestingly, digital progressives are five times more likely to deploy AI in-house, enhancing their expertise and capabilities more than the digital mainstream.  

• But there will not be an AI “wild west.” Most companies have already established guidelines and restrictions for AI development – and plan to increase restrictions in future. In fact, digital progressives are four times more likely to put significant restrictions on employees, meaning they see the most value but aren’t running fast and free.

• Barriers to generative AI adoption remain. Concerns about generative AI’s robustness and its reliability, as well as the availability of needed data and the challenge of access to necessary computational power, stand in the way of continued adoption. 

Survey Results in Detail 

Among the survey’s major findings: 

 “Digital progressives” — who regard their digital investments as a success — expect AI will have high impact on their businesses  

Executives are convinced that AI will make a difference. A strong majority expect it to have a high impact on their industry (57% chose six or seven on an impact scale of 1-7) and on their business processes (57%).   

But there was a sharp split between digital progressives — those that consider their digital investments a success — and the digital mainstream, who are less optimistic (selecting 1-5 on the scale of 1-7). Seventy-five percent of digital leaders expect AI will have a high impact on their industry, and 74% expect a high impact on their business processes.  

By contrast, only 30% of the digital mainstream expect a high industry impact, and only 25% expect a high impact on business processes (see Figure 1).

That optimism seems well founded; AI is having a strong and measurable impact on business performance 

Executives report that their AI investment is producing measurable results. Asked to rate the performance impact of their AI investment by KPI relative to their KPI targets, the executives we surveyed cited reduced customer acquisition cost (23.3%) and increased lifetime customer value (13.6%), and customer count (10.7%) (see Figure 2).

Marketing and personalization get the hype, but AI adoption is broader than that 

The generative AI hype cycle has created a skewed impression. If media coverage is to be believed, marketing and personalization are the dominant areas for AI adoption to date. But our survey results don’t bear that out. More than half of the executives reported they are already using AI (generative and otherwise) in a wide array of functions, including marketing and customer engagement but also scientific discovery, product R&D, pricing optimization, process automation, frontline employee empowerment and back-office enablement, among others. The biggest areas for current adoption were supply chain visibility (65%), planning, procurement and execution (64%) and enterprisewide process automation in nonmanufacturing settings. But no area of current deployment saw a lower level than 56% (see Figure 3).

Plans for future adoption — two years from now, in 2025 — are equally extensive. But expected adoption rates are even higher, with many areas of focus cited by more than 70% of executives. The results suggest that AI will become a bigger factor in customer engagement and personalization, with 72% reporting they expect to use AI two years from now in marketing and promotional applications, an increase of 13% from today. Other functions where executives expect increase adoption include product research, development and launch (77% two years from now, a 15% increase), channel expansion (75% two years from now, a 17% increase), and pricing optimization and product profitability (71% two years from now, a 14% increase) (see Figure 4). 

Some executives expect that AI will eliminate some jobs — but more expect the primary result to be enhanced productivity 

As focus on AI intensifies and public debate begins, one pressing concern is whether AI will replace jobs — or even whole categories of employment. And a significant number — 39% — of the executives we surveyed expect AI to replace some jobs. But substantially more than half — 61% — expect that AI will enhance productivity but not reduce headcount. The biggest areas where productivity enhancement is expected: Salesforce effectiveness (67%), frontline and production employee empowerment (65%) and customer engagement and personalization (65%). Forty-six percent expect that process automation in nonmanufacturing settings will lead to job reduction (see Figure 5).

Executives who are building AI capabilities don’t plan to go it alone — but most will make some use of in-house resources 

Executives see multiple paths to building AI capabilities, but most (71%) plan to make at least some use of third-party resources. Only 33% plan to develop AI using only in-house developers. Where we see some difference is that digital progressives are five times more likely to invest in in-house development of AI, developing the muscles that that the digital mainstream aren’t (see Figure 6).

When it comes to the adoption of generative AI, executives see more barriers 

Asked specifically about generative AI, the executives we surveyed saw a number of barriers to its adoption. Data robustness and availability for generative AI is the most-cited barrier — 18% called it the number one barrier to adoption and 46% rated it as number one, two or three. Other barriers include intellectual property protection, as well as the amount of expertise and resources available (see Figure 7).

But here again, there were sharp differences between digital progressives and the digital mainstream. The barrier most cited by digital progressives was data avaliability. The digital mainstream, on the other hand, raised the issue of the availability of expertise and resources (44%) as well as cost and return on investment (34%) (see Figure 8).

When it comes to concerns about generative AI, executives are taking the lead; they are already deploying guidelines for generative AI deployment in an effort to rein in risk for their organizations 

The executives are aware that there are risks to unrestricted, “runaway” AI deployment. They are already putting safeguards in place to govern generative AI deployment. More than half — 57% — have established restrictions on generative AI backed by formal guidelines. Twenty-eight percent described the restrictions as “significant.” Digital progressives are four times more likely to be establishing "significant restrictions"—  meaning that those who see more potential and are moving faster, are still doing so in a calculated way, with governance and structure (see Figure 9).

Despite concerns about generative AI, the future of AI overall — as measured by expected investment — seems robust 

Whatever the concerns about generative AI, the survey suggests that expansion of AI overall will be robust, with both digital progressives and the digital mainstream expecting to spend heavily. Fifty-six percent of the executives reported that their companies plan to make significant or high investment in AI (see Figure 10). 

AI adoption varies by industry: financial services, healthcare and TMT are farthest along the adoption curve, but other industries are gaining ground 

It should not come as a surprise that AI adoption levels vary widely by industry. Healthcare and financial service are the clear leaders, deploying AI across a wide variety of functions. Technology, media and telecommunications (TMT) is another strong adopter and uses AI across the most strategies — with a particular focus on optimizing sales reach, improving supply chain management, meeting business objectives and increasing resilience. Adoption in the consumer and industrials sectors lag — but planning and exploration are well underway. Consumer and industrials focus on obtaining and managing data to inform AI deployments.

Conclusion 

What should decision-makers conclude based on these survey findings? First and foremost, that they can expect their AI investments to pay off. Companies are exceeding their targets across multiple KPIs – not only reduced customer acquisition cost and increased long-term value — as a result of their AI investment.  

That said, the level of investment required is significant if the goal is to turn AI deployment into real business results. The central challenge is to ensure that investments align with strategy, are fit for purpose, provide meaningful impact, and leverage the right mix of in-house development and the AI ecosystem of developers and capabilities. A careful and critical review of AI strategy — supported by expertise and experience — is essential if the organization’s steps on the AI path are to lead to success.

For more information, please contact us at strategy@lek.com. 

The authors would like to acknowledge L.E.K.'s Digital Practice members Ryan Moore, Julie Sussman, and Sophie Sun for their support and effort in authoring the survey and study. 

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