Big Tech’s AI Ambitions Face Reality Check, PYMNTS Report Shows

Despite big budgets and bold plans, a new survey conducted by PYMNTS Intelligence reveals most large companies are struggling to implement AI in meaningful ways, lagging behind in the race to leverage artificial intelligence for transformative business impact.

The findings detailed in “The Impact Of GenAI on a COO’s Priorities,” the third edition of PYMNTS Intelligence’s “2024 CAIO Project,” offer a sobering reality check for the AI revolution. Surveying chief operating officers from companies with at least $1 billion in annual revenue, the report uncovers a significant gap between the perceived potential of generative AI and its current applications in the corporate world.

“Seventy percent of COOs from firms surveyed — all with at least $1 billion in revenue — agree that GenAI is a critical part of strategic planning,” the report stated. “Nonetheless, there is a gulf between aspiration and reality.”

This disconnect between vision and execution is particularly striking, given AI’s high-profile nature in today’s business landscape. With tech giants and startups alike touting its transformative power, many had expected to see more rapid and widespread adoption of advanced AI applications in large enterprises.

Mundane Tasks Trump Strategic Applications

Instead of leveraging AI for high-level decision-making or innovative product development, many companies deploy the technology for more routine tasks. The survey found that “nearly 6 in 10 COOs (58%) say their firms use GenAI for accessing information, while half of the executives say they use it with chatbots for customer service.”

This focus on less complex applications extends to other areas as well. The report noted that 53% of COOs use AI technology to create data visualizations. However, the effectiveness of these applications varies, with 22% of respondents indicating that GenAI was not highly effective for this purpose.

The tendency to prioritize mundane tasks over more strategic applications is particularly evident in certain key business areas. “COOs are less likely to credit GenAI as necessary for production purposes, such as managing inventory or running logistics,” the report states. “Just 35% of COOs say GenAI is highly important for HR management and logistics.”

This cautious approach to AI implementation may stem from a need for greater familiarity with the technology’s full capabilities. The survey revealed that 38% of COOs consider familiarizing themselves with the complete range of AI possibilities a drawback to implementation.

Strategic AI Use Yields Higher Returns

While many firms are playing it safe with their AI deployments, the report suggests that this conservative approach may limit their potential returns on investment. The report finds a clear correlation between strategic AI use and positive financial outcomes.

The report showed that “29% of the firms using the technology in highly impactful and strategic ways report very positive ROI.” However, in contrast, “just 8.8% of firms using GenAI for more routine and less impactful tasks reported positive ROI.”

This disparity in outcomes highlights the potential benefits of more ambitious AI strategies. Companies willing to trust AI with more complex and consequential tasks reap greater rewards.

One example of this disconnect between potential and actual use is in code generation. The report classifies this as a “medium impact” strategic use of AI, noting, “Although using the technology for code generation was highly effective according to all those who used it, just 18% of COOs reported generating code with GenAI.”

AI Reshapes Workforce Needs

Beyond its impact on business processes and financial outcomes, the adoption of AI also significantly affects workforce composition and skills requirements. Contrary to fears of widespread job losses due to automation, the survey suggests that AI is driving a shift in labor needs rather than simply eliminating positions.

The report found that “88% reported that their organization’s need for analytically skilled workers has increased.” This surge in demand for analytical talent comes even as “42% of COOs agree that using GenAI has decreased the company’s need for lower-skilled workers.”

This shift in workforce requirements presents challenges and opportunities for companies and employees. Firms may need to invest heavily in retraining and upskilling programs to ensure their workforce can effectively leverage AI technologies. Meanwhile, workers with strong analytical skills may be in increasingly high demand.

The focus on analytical skills aligns with the broader trend of data-driven decision-making in modern business. As AI systems generate more insights and predictions, companies need employees to interpret this information and translate it into actionable strategies.

Measuring AI’s Impact

Despite the challenges in implementation, COOs remain optimistic about AI’s potential to drive efficiencies and reduce costs. The report showed that executives primarily focus on efficiency-related metrics when assessing their AI investments.

“Nearly all COOs surveyed, 92%, report using at least one measure of investment return that focuses on cost reduction, such as reduced operational costs, capital expenditures or headcount,” the report stated. This emphasis on cost-cutting metrics outweighs increased profits or market expansion measures, with only 70% of COOs citing profit-related measures of AI success.

This focus on efficiency gains may explain the current preference for using AI in more routine tasks, where the impact on costs is more immediately apparent and easier to quantify.

Looking Ahead

As companies continue to navigate the AI landscape, those who can effectively leverage the technology for strategic purposes may gain a significant competitive advantage. However, realizing this potential will require overcoming implementation hurdles, rethinking traditional approaches to workforce management, and taking calculated risks with more ambitious AI deployments.

The report concluded, “The opportunity is ripe for larger firms to focus their AI use in highly impactful ways and employ more analytically skilled workers to fill the gaps they are currently experiencing.”

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