Podcast
November 21, 2025
Episode 68: Shiny Objects, Dull Outcomes - Navigating the AI Tool Craze
One RevOps leader shares tactics to tackle AI shiny object syndrome: how to separate hype from real impact and use AI where it actually drives revenue.
In this episode of the RevOpsAF Podcast, co-host Camela Thompson, Head of Marketing at RevOps Co-op, sits down with Jeremy Steinbring, Founder and CEO of RevOnyx, to dig into one of the most pervasive and costly challenges facing modern revenue operators — AI Shiny Object Syndrome.
From the explosion of “.ai” rebrands and inboxes full of “revolutionary” automation tools to leaders chasing shortcuts instead of fixing broken processes, this episode unpacks the harsh truth behind the hype cycle. Camela and Jeremy get real about what AI can do, what it can’t, and why so many RevOps teams are burning cycles, credibility, and budget in pursuit of the next shiny thing.
Every operator has felt it — the creeping pressure to adopt the “next big thing” before the competition does. Jeremy defines shiny object syndrome as anything that looks innovative but fails to move revenue, whether that’s a new AI feature buried inside your CRM or yet another analytics add-on pitched as “revolutionary.”
“If it doesn’t work manually with a human doing it, no tool is going to fix that problem.” – Jeremy Steinbring
The pattern is predictable: a vendor markets a feature as transformational, a VP of Sales or Marketing insists on trying it, and RevOps inherits another system to connect, measure, and maintain. The problem isn’t the technology itself — it’s chasing novelty over impact.
Camela likens it to crash-diet culture: “Instead of doing the hard work of building healthy processes, teams want the quick fix. But the short-term hit never lasts.”
For operators already stretched thin between system maintenance, analytics, and enablement, shiny object syndrome compounds the chaos. More tech, more data, more silos — and still no meaningful lift in pipeline velocity or conversion.
For more on avoid tech stack fiascos, check out the RevOps Co-op Video Series: The Keys to Optimizing Your Tech Stack and Avoiding Fiascos.
The current AI gold rush has amplified this issue tenfold. Companies are literally renaming themselves with “.ai” domains to ride the wave. Product marketers oversell immature features; execs panic-buy in hopes of staying relevant. Jeremy calls it the “AI diet pill” — a seductive promise of effortless transformation.
“People are treating AI like the weight-loss pill for revenue. They think it’s going to fix everything without side effects. It’s a bandaid for deeper operational problems.” – Jeremy Steinbring
Instead of using AI to optimize proven workflows, many teams apply it to broken systems — automating messy data, unvalidated outreach, or half-baked messaging. The result? Scaled inefficiency.
Camela points out the irony: “We’re using AI to accelerate the very problems RevOps is supposed to solve.”
Jeremy breaks AI’s utility into two bookends of the GTM motion — where data is abundant, context is clear, and human nuance is less critical.
This “hallucination problem” means RevOps leaders must stay skeptical. Automating analytics without human validation risks turning dashboards into fiction.
For more on AI Orchestration, check out the RevOps Co-op Video Series: AI Orchestration: Infrastructure Behind AI That Works.
Camela, who has lived deep inside RevOps data stacks, notes that most companies lack the data hygiene to make AI useful. AI thrives on pattern recognition; if your CRM fields are mislabeled, your attribution inconsistent, or your duplicates unresolved, it will amplify those flaws.
“AI doesn’t know the difference between incomplete and incorrect — it just assumes confidence.” – Camela Thompson
The danger isn’t just in bad dashboards; it’s in decision-making. When leadership believes the machine, RevOps loses its credibility as the “source of truth.”
Jeremy advises clients to treat AI as an accelerant, not an architect.
“If you put bad data in, AI just lets you make bad decisions faster.”
For more on what CRM Admins should know about Marketing Automation, check out the RevOps Co-op Blog: What CRM Admins Should Know About Marketing Automation.
Ironically, the more AI infiltrates go-to-market motions, the more valuable genuine human connection becomes.
“Everything online feels fake right now. That’s why community and in-person events are booming — they can’t be automated.” – Jeremy Steinbring
Both Camela and Jeremy agree: the pendulum is swinging back toward in-person dinners, community-driven engagement, and experiential marketing. With email deliverability plummeting and inboxes flooded with AI-authored spam, operators who invest in authentic relationships — not automations — are cutting through the noise.
In fact, Jeremy predicts that the future of RevOps will look more like relationship engineering than system administration: “It’s not about who can send more emails; it’s who can build more trust.”
To join the largest community of revenue operators on the face of planet earth, check out the RevOps Co-op membership options.
One overlooked side effect of the AI boom is lower barriers to entry. With no-code and AI builders, anyone can spin up a SaaS product in weeks. That explosion of micro-competitors means existing players face more churn risk than ever before.
“It’s easier to start a company, so it’s easier to lose a customer.” – Jeremy Steinbring
This dynamic shifts the growth imperative. Instead of chasing new logos through expensive outbound campaigns, smart operators are doubling down on retention, expansion, and advocacy — the right side of the bowtie revenue model.
Jeremy observes that companies that emphasize customer evangelism and lifecycle health are outperforming those obsessed with net-new acquisition.
“Everyone says they care about expansion, but most budgets still go to prospecting tools, not retention.”
For more on building a lean tech stack, check out this oldie but goodie RevOps Co-op Blog: Your 2025 RevOps Tech Stack, Simplified.
Both guests identify the true driver of AI shiny object syndrome: executive panic. PE- and VC-backed leadership teams, under pressure to sustain unsustainable growth, fixate on “what’s next” instead of “what works.”
“Nobody’s asking, ‘How do we improve retention?’ Everyone’s asking, ‘Where’s the next new revenue stream?’” – Jeremy Steinbring
Camela links this mindset to the burnout epidemic in RevOps: constant reprioritization, unrealistic expectations, and the emotional labor of managing up.
“We spend half our time building dashboards that prove our point and the other half reprioritizing projects that contradict them.”
Jeremy adds that RevOps leaders are often trapped between logic and leadership: “You can show the data, but you don’t write the check.”
For more on leading your team while fighting burnout and department silos, check out the RevOps Co-op Blog: A Framework to Improve RevOps Team Dynamics.
Both guests agree: AI experimentation isn’t the problem — blind adoption is. The key is to explore without restructuring your business around unproven technology.
“Play and explore, but don’t upend your tech stack for the shiny new thing.” – Jeremy Steinbring
Jeremy’s readiness checklist for RevOps leaders evaluating AI tools:
Camela sums it up: “Experimentation should feel like R&D, not like ripping out your GTM engine mid-flight.”
For more on change management best practices, check out the RevOps Co-op Blog: 9 Best Practices for Better Change Management.
The operators who thrive through the AI era won’t be the ones who buy the most tools — they’ll be the ones who:
In other words, the future of RevOps isn’t more automation — it’s smarter orchestration.
For more on the question of Is AI is coming for RevOps, or RevOps coming for AI?, check out RevOpsAF Podcast Episode 29: The AI Impact on Revenue Operations.
AI isn’t a threat or a miracle. It’s a mirror. It exposes what’s working in your systems and magnifies what’s broken.
For now, the smartest RevOps teams are staying grounded — experimenting responsibly, investing in data hygiene, and doubling down on relationships that can’t be automated.
“AI won’t replace RevOps. But the operators who know how to use AI wisely will replace the ones who don’t.” – Camela Thompson
Check out the RevOps Co-op Blog for insights on AI orchestration, data foundations, and change management in modern RevOps.
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