Designit says telecom operators risk focusing on the wrong AI problem, after new survey data suggested that speed of deployment is overshadowing the organisational work required to make the technology deliver at scale.
The global research, conducted by Designit, Wipro’s experience innovation company, found that 43% of design and telecom professionals see rolling out AI too quickly as the biggest mistake telecom companies make when introducing the technology. Treating AI primarily as a cost-cutting tool ranked second at 32%, followed by poor data readiness at 14%, and automating without organisational redesign at 11%.
The results show an industry still measuring AI progress through visible momentum — how quickly tools go live, how many processes they touch, and how broadly deployments can be scaled. Yet the survey also suggests that the redesign needed to support those systems is attracting far less attention.
Designit said that gap is especially significant in telecoms, where operators are managing legacy infrastructure, regulatory pressure, and the operational demands of serving millions of customers. In those environments, AI deployments do not succeed on technical capability alone. Workflows, governance, accountabilities, and team structures also need to change if pilots are to move into stable, cross-functional use.
“Telecoms is one of the most complex environments in which to embed AI. Managing legacy infrastructure, regulatory pressure, and the need to serve millions of customers every day means the margin for a poorly prepared AI deployment is slim,” said Jakob Voldum, insights and strategy design director at Designit. “In many cases, organisations are introducing AI without a clear view of what success looks like. Without that direction, speed only brings misalignment to the surface quicker.”
Designit argued that the core challenge is not technology in isolation, but organisational readiness around it. Companies may be able to deploy tools quickly, but those tools can stall when operating models remain unchanged or when teams are unclear about ownership and decision-making.
“Technology is rarely a problem in isolation. The challenge is in ensuring the organisation is ready to meet it – redesigning workflows, clarifying accountabilities, and ensuring governance and team structures are in place before the pressure to scale arrives,” said Voldum. “Those who will succeed will be those who treat AI as an opportunity to redesign how they operate, not just where they automate. That is where long-term value will be created.”
Designit pointed to its work with Dutch telecommunications provider Odido as an example of that approach. Through an embedded studio model, the company said it worked alongside business and IT teams to bridge the gap between commercial ambition and operational delivery, helping move AI into a scalable, cross-functional capability.
The survey leaves telecom operators with a clear operational question: not how quickly AI can be launched, but whether the business is set up to absorb it once it is live.
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