- The AI adoption challenge is not about technology but the workforce, a Bell Canada exec told us
- Training employees how to adjust to and use AI tools remains a top priority
- Bell is using ServiceNow to simplify network ops and also make AI more accessible for workers
AI is shifting from concept to reality in telecom and the enterprise. But successful adoption doesn’t just mean integrating the technology – it’s about ensuring the entire workforce – not only engineers and IT – knows how to use it, Bell Canada Group President John Watson told Fierce.
As AI applications become more decentralized through agents, open-source models and the like, “it’s not a technology challenge anymore,” he said. “You now need a cultural orientation [and a] talent orientation more broadly…within your company to then go and maximize this moment in time.”
Bell, like other telcos, is using AI to streamline its network, IT infrastructure and customer service operations. With the help of ServiceNow, Watson noted the operator is providing real-time job data, optimized routing and automated scheduling to around 12,000 field technicians.
However, maximizing AI’s potential goes beyond automating customer service and field work. He said companies need to instill a “sense of urgency” in their workforce, adding they can’t just sit around and wait for the data engineering team to “[get] their data done” or for IT staff to build an AI platform.
“Everyone has to be AI-literate and AI-centric in terms of their job and role and they have to be using AI continuously within their capacity, and that is a big change for a lot of organizational people,” Watson explained.
Essentially, he believes AI needs to transition from a specialized role to a “personal skill and a personal way of doing things within a business.”
Easier said than done, as the AI skill gap remains a persistent challenge in the workforce. Although AI is poised to become more user-friendly over time, companies now still need to train employees in how to effectively use those tools, J.Gold Associates Founder Jack Gold previously told Fierce.
Overcoming the skills obstacle is also critical for operators looking to do more in-house AI work with open-source tools and agents.
One benefit of ServiceNow, said Watson, is employees can use natural language for the applications on its platform. “It doesn’t require you to have an expert systems architect and now you’re able to do things, democratizing IT into the business where you’re closer to the customer,” he added.
Data is still the first step for AI adoption
ServiceNow has been a mainstay among large enterprises for its IT service management business, but its AI platform is getting more attention from the telecom industry.
Apart from Bell, BT and Verizon are some of the other big-name operators using ServiceNow to improve network and customer operations. ServiceNow earlier this year revealed AI agents tailor-made for telcos so they can better handle copious amounts of data.
Unlike other industries, telecommunications companies have “so much data that exists already in the organization,” said Rohit Batra, ServiceNow’s GM and VP of manufacturing, telecom, media & technology. ServiceNow uses a technique called “zero-copy” to help companies directly access data from external sources, so they don’t have to physically move it or re-format it for multiple platforms.
Aside from creating agents that can automate things like customer maintenance requests and billing inquiries, ServiceNow is also working on use cases like agent-to-agent integration, where AI agents from different vendors and enterprises can essentially talk to each other.
But these use-cases and other innovations in AI don’t mean much unless you get past the initial data roadblock.
“You can build AI but if you build AI on a crappy workflow without having access to the data, it just becomes an automated AI agent that does not do optimal work,” Batra said.
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