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Many technology leaders are skeptical or worried about the use of artificial intelligence tools. At the same time, organizations rely on these tools to handle more and more roles and functions. Given this paradox, an important consideration is what is needed to align these two opposing dynamics.
A recent survey of 1,393 technology leaders from 9 countries by IT staff and service provider Experis showed that around two-thirds of technology accelerated AI capabilities, and about half incorporate AI skills into existing roles rather than creating new positions.
Yet despite ongoing topics around AI, this study showed a measured approach to AI adoption among technology leaders. Only 37% view generation AI as a valuable solution for certain applications today, while 33% remain uncertain about its business impact.
“CIOs and technology leaders primarily embedding AI into existing capabilities and roles, primarily by expanding existing work patterns and tasks,” says Cameron Haigh, an analyst at research firm Gartner. “This initial use of AI tools is expected to produce moderate productivity gains. In the short term, AI will work within boundaries and enhance the current process without fundamentally converting.”
According to Kye Mitchell, president of Experis Us, companies use AI in several key areas. Enhance cybersecurity through real-time threat detection and response. Improve customer support and sales by streamlining ticket handling and personalized outreach.
Over time, AI tools are expected to be able to push boundaries, become more “agents” and destroy complex problems, Haight said. “This will transform work patterns by allowing developers to fully automate and offload more tasks,” he said.
AI agents can improve developer experiences and improve their ability to deliver business value, Haight said. “AI agents, for example, can automate tasks such as code generation, debugging, and tuning performance,” he said.
Gartner's research has a more nuanced view of AI replacing humans for work, but Haight said the impact is complex and different. “There's speculation and hype from vendors promoting “AI-based software engineers” that replace human engineers, but I believe that, for example, rumors of software engineers' end mise are very exaggerated,” he added.
IT leaders' skepticism and uncertainty about the business impact of AI is partly because many organizations struggle to translate AI investments into tangible productivity improvements, Haight said.
Achieve alignment
To navigate the balance of AI hype, possibilities and challenges, technology leaders need to focus on strategic integration, workforce adaptation, and cultural change, Haight said.
Companies need to shift their focus to an AI-first mindset. “Instead of developers coding everything manually, cultivate an “AI-first” mindset where AI agents focus primarily on maneuvering, by providing software engineers with the mostly relevant context and constraints,” Haight said. “This means a high-class team with high-rich power generation skills in rapid engineering and search.”
Haight says that organizations need to invest in AI developer platforms, particularly in order to build AI-Empowered applications and effectively leverage them to support new roles such as AI engineers. “These platforms provide the necessary technology, workflows, reusable components, access to large-scale language models, and support responsible AI practices, enabling efficient and scalable AI integration,” he said.
The impact of AI requires a role redesign, explaining changes in demand and changing demand, Haight said. “In addition to replacing roles, it focuses on frequently reshaping roles into assisted, multiskilled generalist roles that automate everyday tasks,” he said. “Setting up more networked and dynamic teaming makes it easier for people to connect to their work.”
To align AI enthusiasm with its business impact, technology leaders need to “create spaces for innovation without losing control,” Mitchell said. “That means setting up a secure sandbox to test AI, building a bridge role that connects technology to business, and building a bridge role that measures real outcomes as well as hype. Equally important, it means that AI needs to upskill the team to be a productivity partner, not a mystery or threat.”
Additionally, to bridge the gap between AI deployment and executive hesitation, technology leaders need to focus on small strategic deployments that demonstrate measurable business value, Mitchell said.
“Whether it reduces customer service resolution times or speeds up code reviews, pilot programs with clear KPIs [key performance indicators] Mitchell can turn AI from a buzzword into a business tool.
At the same time, businesses need to implement strong AI governance to monitor how tools are trained, deployed and evaluated, especially in industries where bias and errors have significant consequences.
“And perhaps most importantly, leaders need to take people into the process,” Mitchell said. “AI solutions co-created with inter-duty teams can help build trust, improve outcomes, and turn the story from fear to empowerment.”
While some jobs, such as data entry, low-level coding and everyday legal review, are vulnerable to automation, the future is bright for its role in merging human judgment with machine intelligence, Mitchell said. “Think of AI engineers, data ethicists, cybersecurity experts, and product leaders who know how to build with AI as well as AI,” she said. “The new era of work belongs to people who can't compete with machines and can work with them.”
