How Akamai’s CIO Balances Enthusiasm and Caution in Adopting AI Technology
By John Kell | Fortune
Kate Prouty, Senior Vice President and Chief Information Officer at Akamai Technologies, is navigating the rapidly evolving landscape of artificial intelligence (AI) with a blend of enthusiasm and pragmatic caution. Akamai, a leading player in cybersecurity and cloud computing, has witnessed a surge in employee demand for AI tools and skills, but Prouty is keenly aware of the challenges and risks inherent in embracing new AI technologies at scale.
The AI Tsunami at Akamai
“The demand for AI is out of control,” said Prouty, describing a wave of enthusiasm among Akamai’s global workforce of over 9,000 employees. She notes that employees believe those with stronger AI capabilities will gain a significant competitive edge — a sentiment echoed across the tech industry.
Following the generative AI boom that began in late 2022, Akamai initially embraced what Prouty calls a “thousand flowers bloom” approach. The company provided employees with safe, internal “sandbox” environments to experiment with various AI tools and use cases. While none of these experiments were intended for full-scale production, the strategy fostered creativity and hands-on exploration.
However, as the AI landscape matured, Prouty’s perspective shifted toward a more centralized and controlled approach.
Centralizing AI Efforts for Measured Results
With 26 years of experience at Akamai, Prouty emphasizes the importance of avoiding chaotic proliferation of AI projects across the organization. “It didn’t make sense to me as a CIO to have people developing AI and copilots throughout Akamai’s ecosystem without oversight,” she explained.
Today, Prouty’s team prioritizes partnerships with established vendors—including Cisco, Salesforce, and Google—and closely evaluates pitches from a wide range of AI startups. This evaluation process helps Akamai understand the capabilities, innovation roadmaps, and potential internal adjustments required to effectively leverage AI solutions.
When Akamai decides to integrate an AI feature, it does so with a highly measured rollout. The company runs small pilot tests with several vendors to carefully assess how each technology might benefit their operations, while keeping a close eye on costs and technology maturity. Prouty admits that some AI vendor cost models remain “murky,” causing caution in adoption.
Real-World AI Use: Successes and Challenges
One of Akamai’s successful AI implementations is the controlled release of GitHub Copilot for its software engineers. This tool has accelerated certain projects dramatically, cutting timelines from weeks to hours in some cases. Yet, Prouty acknowledges a learning curve—AI-generated code sometimes contains errors that require manual correction.
Beyond GitHub Copilot, Akamai is exploring other AI coding assistants such as Cursor and Anthropic’s Claude. Still, Prouty insists on clear metrics around productivity gains before greenlighting broader adoption.
For particular niche functions, Akamai has invested in building AI tools in-house. For instance, in partnership with French AI startup Dataiku, the company developed a sales team chatbot that combines OpenAI’s large language models with Akamai’s proprietary data. This tool helps salespeople rapidly gather public and private customer insights before client pitches.
Despite the excitement around “agentic” AI—the next wave of autonomous AI agents expected to peak in 2025—Akamai remains cautious. “I just don’t know if the technology is there yet,” Prouty said, signaling a wait-and-see approach.
Open Doors and Cost Controls: A Balanced AI Strategy
Though the IT department has tightened control over AI deployments, Prouty advocates maintaining an open-door policy for new AI ideas. “Let’s encourage, not discourage,” she said. Employees are invited to propose AI use cases, for which Prouty’s team provides secure frameworks and oversight, including cost controls to prevent runaway spending.
Akamai also fosters collaboration and feedback on AI pilots by creating team chat channels in Webex. This transparent communication allows employees to share what’s working and what isn’t, informing future decisions.
Broader Industry Context
Prouty’s approach reflects a broader industry trend where companies seek to balance AI’s transformative potential against risks of immature technology and unpredictable costs. A recent PagerDuty survey of 1,500 IT executives found that nearly three-quarters consider AI essential to their operations, with many deploying multiple AI agents. However, 85% also reported challenges in detecting AI failures, highlighting ongoing reliability concerns.
Leading tech firms like Salesforce and Broadcom are advancing AI integration, while Meta aggressively recruits AI talent to push innovation. Still, many organizations, including Akamai, remain cautiously optimistic, piloting AI extensively but restraining full-scale rollouts until maturity and value are clearer.
About the Author:
John Kell is a contributing writer for Fortune and author of the CIO Intelligence newsletter.
For feedback on this story or to share AI adoption insights, contact him through the CIO Intelligence platform.
Additional AI Industry Updates:
- Salesforce recently launched Agentforce 360, a platform aimed at simplifying AI agent deployment for enterprise customers.
- Meta Platforms re-hired AI researcher Andrew Tulloch, co-founder of Thinking Machines Lab, highlighting ongoing AI talent competition.
- Broadcom secured a multi-year deal with OpenAI to develop custom chips supporting AI infrastructure needs, signaling strong commercial interest in AI hardware.
This article is part of an ongoing coverage series on AI innovation and enterprise adoption featured by Fortune.
