We are deep in the AI hype cycle. Generative AI, LLMs, Agentic AI - buzzwords dominate the headlines. Gartner defines this cycle as the journey from inflated expectations to disillusionment before reaching meaningful, practical use. That’s where we are now.
But let’s not forget, AI isn’t new. IBM Watson made headlines as far back as 2004 and famously won Jeopardy! in 2011. The novelty isn’t the tech; it’s the marketing surge and the avalanche of claims that AI will replace call centers, SDRs, and more. Maybe it will - eventually. But right now, all the hype is backfiring, especially when it comes to selling.
Here are the three big reasons why:
1. Buyers Are Confused
Surveys are divided: some say AI boosts productivity; others call it delusional. Many businesses are caught in the middle, unsure of what’s real. In any tech adoption curve, most customers are not early adopters. They’re risk-averse and wary of change. Selling cloud services is already hard, you’re asking a business to abandon a system they’ve used for years. Selling AI? Even harder. It’s change on steroids.
2. FOMO Leads to Paralysis
Becomes the Future PBX dealers once dominated business telecom. They sold, installed, trained, and maintained systems. When UCaaS emerged, many assumed they were obsolete. Wrong. Turns out, the skill set didn’t die—it evolved. Businesses still want hands-on implementation, training, MACD, and Tier 1 support. The PBX dealers who realized this pivoted and are now charging multiples over the $13-per-seat nonsense.
3. AI Still Requires Strategy and Structure
The idea of a magical AI agent answering every customer question sounds great, until you realize it needs structure, data, and a solid plan. Anyone who’s ever built a website, an IVR system, or a reporting dashboard knows it’s not plug-and-play. AI is no different. Strategy, architecture, and accessible data are prerequisites, and most small businesses aren’t ready.
In fact, many don’t even have usable data. Even larger enterprises are stuck with siloed or unstructured data that AI can’t digest. No data, no insights. It’s like trying to run a restaurant without ingredients.
We’ve been here before. Think of that complex IVR system that had to be mapped out, step by step. Who’s calling? What do they want? What data powers the experience? The same logic applies to AI - just more complex, with higher expectations.
To move forward, businesses need more than buzzwords - they need concrete use cases that clearly explain what problem is being solved, for whom, and how. And let’s not forget: users typically only tap into 10% of Microsoft Office’s features. Adoption has always been a challenge - and with AI, it’s likely worse.
Want to Sell AI? Make It Simple
If you’re selling AI, treat it like a band-aid: easy to apply, obvious in value, and clearly better than the alternative. That means:
- Focused, low-risk use cases
- Clear ROI within weeks, not years
- Pre-configured outcomes with minimal setup
Until then, the hype might just be your biggest competitor.
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https://www.netsapiens.com/partners/
Peter Radizeski Biography
Peter Radizeski is a veteran of the US Telecoms Channel based in the Sunshine State of Florida. He has assisted numerous prominent service providers across the United States in growing their businesses by offering guidance on sales training, marketing, channel development, and business strategy. He is a reliable source of knowledge about the telecom industry. His candid and straightforward Channel Playbook Blog is essential reading for industry insiders, and he is a sought-after speaker and moderator at industry events.