The AI explosion changed everything. Arguably, not since the advent of the personal computer itself has a technological development catalysed such sweeping and rapid change across the business world. OpenAI’s ChatGPT catapulted AI to the forefront of the mainstream public, and its momentum has only snowballed since then.
Every tech giant, from Microsoft to Google, has incorporated several AI-powered products and services across their vast ecosystems, while almost every other UC and collaboration vendor has released at least one an AI-driven solution. Practically every knowledge worker organisation across the planet has at least dabbled with AI, with many jumping in with both feet into deploying it across their organisation in myriad capacities.
It’s changed the we work and think about working forever.
However, as with any colossal trend that takes the discourse by storm, there have been AI sceptics. Worries about job displacements, as well as data and compliance infringements, are well-documented and valid concerns about AI more broadly. But even organisations supportive of how AI can theoretically boost productivity and collaboration while cutting costs have expressed concerns about erratic user adoption, befuddling complexity, and often steep implementation costs.
It’s why ULAP Networks launched ULAP Voice with the pitch that it’s an AI-free UCaaS solution that is cost-effective, globally compliant, and customised and simplified to meet standard telephony requirements. ULAP clearly identifies a market for AI-free solutions.
Is this AI whirlwind all a little bit too much, too fast? Is there the substance of an AI backlash?
“I think the AI hype has gotten a little overwhelming,” Irwin Lazar, President and Principal Analyst for Metrigy, told UC Today at UC Expo. “In my conversations with IT leaders, they want real results, they want real solutions, they don’t want just to hearar ‘Oh yes, we have AI.'”
“I think you’re seeing that walking around the show floor and talking to some of the vendors here. There’s a lot less stress around being an AI company than there is about providing tangible solutions to deliver and improve customer service, improve communication and collaboration internally and generate gains in productivity and revenue increases. Things you can actually measure.”
Does Jon Arnold, Principal Analyst at J. Arnold & Associates and industry expert, agree?
“For sure,” Arnold told UC Today at UC Expo. “We know AI has been the big trend in technology, not just in the comms space, but everywhere. As far as ‘backlash’ goes, that might be too strong of a word, but one of the big issues is most top management teams, like at the top-down level, are saying, ‘We have to have AI. Our shareholders need to see we have AI. Our customers need to see we have AI. Our partners need to see it.'”
“There’s a bit of a top-down anxiety about being in the game, being with the latest technologies,” he expanded. “At the same time, those on the floor who make the decisions and have to implement and manage them can only go at a certain pace. They have to acquiesce to what’s needed for the business, yes, but the reality of getting it done is much different. There’s a lot of caution, not just about the technology itself but how it fits into everything they’re doing.”
“IT folks have a lot of fires to put out all day, and this is a big one, so they can only realistically handle so much.”
It’s not just about the IT teams, either. Business user managers and workers who aren’t necessarily at the cutting edge of tech savviness might struggle to adjust to the rapid change of AI deployment across the organisation. Those challenges are complemented by the complexity around AI’s interactions with security and compliance, which can be rendered even more convoluted by how rapidly AI products and services are evolving.
“Then there’s dealing with some of those security, compliance, analytics and adoption issues that companies are facing as they are rolling out these solutions,” Lazar said. “Getting them in the hands of people, teaching them how to use it, level-setting expectations around what it can and can’t do, and determining whether or not you’re seeing that value that it promises.”
Arnold agrees that education and patience are critical to successful adoption, as many workers, leaders, and even organisations are still suspicious or uncertain about the technology.
“Of course, there’s also the issue of how to educate people,” Arnold said. “There’s still a trust factor with AI, no matter how you cut it. There’s a lot we don’t know about AI, and there’s a lot that end users don’t know or trust about AI. That’s a longer process. There’s a fundamental issue where the technology is moving faster than organisations’ ability to absorb it. There’s a big disconnect there right now that’s continuing.”
“That’s why there’s a bit of a backlash,” he continued. “‘We can only go so fast. We can only carry so much in our hands at once.’ But that’s natural. That’s part of the hype cycle at play, but it will smooth out eventually, especially once they start seeing results that make sense for people and we level our expectations.”
