71% of Services Firms Cite AI Skill Gaps

Just months before Block’s dramatic announcement of letting go of 40% of its workforce, a growing number of large companies said they were ready for artificial intelligence (AI), yet many admitted they were still writing the workforce playbook as they went.

That is the central tension in PYMNTS Intelligence’s report, titled “No Roadmap, No Problem: How Enterprises Are Reinventing the AI Workforce.” The study, based on a survey of 60 CFOs at U.S. firms generating at least $1 billion in annual revenue, finds that AI has moved from experimentation to active integration. Companies are pushing ahead. But preparation for how AI will reshape jobs, skills and management structures remains uneven.

The report shows that there is no single blueprint for how enterprises are deploying AI. Instead, industry priorities drive strategy. Goods producers lean into productivity. Services firms emphasize decision-making. Technology companies focus on maintaining an edge. Across sectors, CFOs agree that AI will not simply automate tasks. It will redistribute work and redefine roles.

Several data points stand out:

34% of CFOs cite increased output as their top motivation for introducing AI, while 24% point to staying competitive and 19% prioritize enhancing decision-making with better data insights.

50% of CFOs expect AI to create new job roles requiring new skills, even as 47% anticipate significant headcount reductions.

60% say their firms are at least somewhat prepared for AI-driven workforce change, but only 12% describe themselves as very prepared.

Beneath those headline figures lie a more nuanced shift. The divergence across sectors is striking. In goods industries, 48% of CFOs say boosting output is the primary driver. In services, 30% prioritize better decision-making. In tech, 42% focus on competitiveness. These are not minor variations. They reflect fundamentally different views about where AI delivers value.

The readiness gap is just as revealing. Tech firms report the highest level of confidence, with 75% of CFOs saying they are at least somewhat prepared for AI’s workforce impact.

Goods firms follow at 63%. Services firms trail at 48%. That lag may reflect heavier dependence on human judgment and client interaction, areas where AI integration can be more complex.

CFOs also see risk. Nearly two-thirds cite increased operational complexity as a major concern, and 58% point to skill gaps. In services, that figure rises to 71%. Employee resistance, reputational considerations and legal exposure also rank high. The message is clear. Implementation is hard.

Yet the tone of the report is not alarmist. Most CFOs, about 65%, describe AI’s workforce impact as mixed, balancing gains and disruptions. Only 3.3% see it as negative overall. That suggests executives recognize both the friction and the upside.

What emerges is a picture of enterprises in transition. AI adoption is no longer theoretical. It is embedded in hiring strategies, role redesign and automation plans. Some firms are recruiting new AI talent. Others are redesigning workflows to blend human expertise with machine support. Many are doing both.

The absence of a universal roadmap may be less a weakness than a sign of adaptation. Industries are tailoring AI to their economic realities rather than forcing a one-size-fits-all model. That flexibility could prove to be a competitive advantage over time.

The next phase will hinge on execution. Skill development. Change management. Clear governance. Companies that invest in those foundations are more likely to turn early experimentation into durable performance gains.

At PYMNTS Intelligence, we work with businesses to uncover insights that fuel intelligent, data-driven discussions on changing customer expectations, a more connected economy and the strategic shifts necessary to achieve outcomes. With rigorous research methodologies and unwavering commitment to objective quality, we offer trusted data to grow your business. As our partner, you’ll have access to our diverse team of PhDs, researchers, data analysts, number crunchers, subject matter veterans and editorial experts.