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As AI adoption moves at breakneck speed, technology leaders have had to adapt how they own and deploy tools within their organizations.
Many executives feel pressured to find the next thing. Improving pilot productivity and said he would understand the project financially. Babak Hodjat, chief AI officer at consulting firm Cognizant. CIOs, CTOs, and chief AI executives must now think beyond technology and innovation to propose enterprise-wide roadmaps and strategies.
He said the change has placed more focus on technology leaders in the C-suite.
“In a world of rapid AI innovation and disruption, how can you stay ahead of the competition?” Hojat Said.
Responsibility for AI adoption and success most often lies with the CIO, CTO, or other technology leader. recent ultimate report Found it. As strategies often change from week to week, the roles and responsibilities of C-suite technology leaders are also evolving.
The CIO has gone from being a behind-the-scenes C-suite member helping people run SaaS platforms to being front and center in identifying use cases for AI. Hojat Said.
Most CIOs say they are highly motivated to drive AI projects and tend to play a supporting role in other parts of the organization. Brian Jackson, Principal Research Director, Info-Tech Research Group. They often become technology experts who create methodologies and integrate them into workflows.
Part of the immediate job for technology leaders, Jackson said, is to assess the maturity of their organizations and ask themselves whether their data and infrastructure is ready for AI pilots, or whether they need to prepare IT to get value.
“We’re not necessarily trying to determine how technology is used and what it should do,” Jackson said. “But because we teach organizations about technology, we can increase literacy, demonstrate competency, and encourage ideas about how to use it.”
While the CTO role used to be focused on research and development, it is now focused almost exclusively on “the next big thing in AI that’s coming,” Hodjat says. These are likely to be more central to corporate strategy and may lead the board to make predictions for the future.
In the era of AI implementation, these technology roles are likely to work more closely with the financial side of the C-suite than before to measure growth and spending on new projects.
owner governance
Technology leaders are responsible for not only implementing AI, but also collaborating on policies and guardrails around how AI is used within their organizations.
Hojat said this process is continuous.
Until recently, guardrails served as a one-time audit, giving a false sense of security, he said.
“Given the adoption rate of today’s AI systems and the autonomy that comes with it, we can’t afford to do that,” Hodjat says.
He added that it can be helpful to think of the enterprise as a modular, multi-agent fabric that continues to expand. Rather than looking at the whole, technology leaders can create governance for each part in a way that works best for the organization.
This approach is especially necessary when working with companies that have multi-model and multi-agent technology stacks, Jackson said.
“The key is really understanding this new architecture, this new governance layer,” Jackson said. “AI is more than just software deployed in enterprises.”
While there are universal checks that technology leaders should perform, each organization must tailor its safeguards to its own AI projects. AI governance will occur at different levels of the organization. Hojat Said. However, governance is best established when there is a clear and proven use case for AI and technology leaders can decide that AI is not needed.
“We tell our clients to put on the brakes a little bit and think: Does your business have an absolute vision of having a bunch of agents running around and doing things semi-autonomously?” he asked. “How do you get there? Some roads are safe, some are not.”
