Leaders are sitting in boardrooms asking, “Can’t AI do that?” and they’re not wrong to ask. A lot of the work we’ve made for ourselves as humans can now be handled by AI, with a few people left to stamp decisions. What does the world look like if everything we’ve built as a so-called stable structure around us doesn’t need us?
Here's what I know: we don't have a choice about whether AI continues to disrupt work as we know it. This means we only have choices about how.
Ticket queues. Data entry. Survey analysis. Spreadsheet monitoring. Email triage. We made all of this up. Humans created this work because we were the most efficient way to process information at scale. That's no longer the case.
I lead AI product strategy. I'm in the rooms where these decisions get made, touching shoulders with people who see headcount reduction as the quick lever to pull. People who believe that just because AI can replace someone, it should. What's on the table for them is margin improvement. What's on the table for me is whether humans get uplifted in this age or left behind.
The opportunity to burn it down and rebuild with humanity at the center is exactly why I'm choosing to influence the future of work in this pivotal moment. Because if I'm not in the room making these calls, someone else will be, and I’m not so certain they care more about humans than they do profits.
The Reality
AI adoption isn't optional for competitive survival. Companies that don't successfully implement AI risk being eaten alive by their competitors who do. Their business likely won't last beyond 2–5 years. This isn't hypothetical. The value AI unlocks is real, and organizations and people alike will get left behind.
However, there’s a scenario that makes that matter even worse.
When the adoption of AI is owned by people chasing efficiency metrics and headcount reduction to maximize gains, we’re not only heading towards the downfall of organizations that don’t adopt in time, but we're heading toward technological displacement at a scale we've only seen in science fiction. This is already happening. Companies claiming AI efficiency gains to justify mass layoffs. Fewer people can do more. Margins will look better. It’s a no-brainer (to the system).
Using my Influence Wisely
When people ask about our future with the advancement of AI, what they're really asking is: "How do we reconcile the risk of job displacement, the disruption of the human role in capitalism as we know it, and what happens when we’re removed from the structure entirely?”
My role gives me the ability to influence how AI gets deployed inside the organization. When decisions are made about what to automate, where to apply AI, and why, I focus the conversation on human value—not just efficiency metrics. At scale, that shift changes the shape of the structure itself.
This influence isn’t about blocking automation. It’s about ensuring we use AI intentionally. Just because AI can do something doesn’t mean it should. And when the answer is yes, the implementation must strengthen people, not sideline them.
Skeptics and Proof Points
There are AI naysayers in my organization. Their fear is rational. Their strategy is not. They're right that AI can displace people, strip purpose from work, and optimize for metrics over humanity. But abstaining doesn't build a career in a world that's moving regardless of their buy-in.
So, I don't start with the skeptics. I start with the team members who see possibility in human-AI collaboration. We build products that demonstrably lift people up, that give them more interesting problems to solve, that amplify their expertise. Those early adopters become proof points.
When skeptics see their peers thriving rather than being displaced, the conversation shifts from "whether" to "how can I be part of shaping this?" Proof beats argument every time.
I can’t force engagement. I can only build proof points and leave the door open. Some people won't walk through it, and I've made peace with that.
The Framework
Humans created this work because we had no better option. That’s no longer the case.
This is the clarity that separates strategic AI deployment from lazy, efficiency-chasing automation. We get to choose if we automate the same jobs into oblivion just because the technology can, or if we should ask why we created that work in the first place and whether there’s better work to create instead.
That’s not a moral question. It’s a strategic one. And it’s the only reason my framework works.
With that as the premise, here’s how I take a strategic eye to every AI initiative that comes into our backlog.
Survival
Required for staying afloat whilst enabling room for growth.
As a managed service provider, we are on the line for providing white glove services to our customers. If someone else can provide that service better, quicker, and cheaper, we’re in trouble. For example, we built a ticket triage system. The system is smart. It reads incoming tickets, analyzes data, understands the problem, and knows which team members can resolve it. The system gets that ticket to the problem solver in seconds.
We could have automated our solution entirely, reducing roles and maximizing the speed of the process. We didn't. This commitment to scale without reducing headcount is an intentional design constraint. We automated pattern recognition and kept human judgment for problem resolution and customer service. Our engineers solve complex problems. AI handles the queue, and humans handle the thinking. This lets us compete and scale with our business without proportionally scaling headcount. The system becomes a capacity creator, not a job eliminator.
The Convenience Trap
High volume, low value, and high computational cost.
AI SDRs waste energy spamming people, eliminate entry-level sales jobs, annoy customers, and damage relationships. High cost, low value, wrong tool.
Scaling laws are in effect here. AI SDRs will make more dials. More dials yield more appointments, and more appointments mean more potential revenue. Companies using AI SDRs today are winning the volume game against companies that aren't. But these companies are optimizing for the wrong metric. They're asking, "How can we make more calls?" and optimizing volume over value.
They're not wrong that AI can execute more dials. They're wrong about what that accomplishes.
The alternative isn't rejecting AI in sales. It's rejecting the convenience framing and asking a different question: what if AI fundamentally reimagined what an SDR does? Less time on data collection and list building, more time on actual relationship intelligence. Fewer calls, better conversations, real appointments because we're solving for prospect needs instead of chasing volume. That's not convenience. That's growth.
Growth
Addresses critical risks, especially those AI itself creates.
While others are using AI to cut costs by replacing human labor with agents, we're using AI to grow our people through the disruption.
The SDR reimagination I mentioned above? We're building it. Less volume, better conversations, AI handling the research so humans can handle the relationships.
But the bigger bet is an assessment platform that develops a new kind of role entirely. Previously, assessments were siloed – one person, one client, one report. The work was reactive, and the expertise was narrow. Now, AI surfaces patterns across our entire customer base. Our people see connections they couldn't before: what's working elsewhere, what's coming, what this client doesn't know they need yet. They're not going through the assessment process motions, crossing their fingers for conversion. They're building expertise that compounds, becoming the people who see around corners.
This isn't efficiency. It's development. We're growing AI-enabled roles that didn't exist before, where the ceiling keeps rising because the work keeps getting more interesting. Job descriptions in this space are going to look different. We're giving people the tools to shape what that looks like for them rather than having it happen to them.
Designing With, Not For
When evaluating opportunities to partner our people with AI, they are in the room. Where do they thrive? Where does their existing value and future potential live? What could value look like if all constraints were removed? We design a future that weaves together AI and human expertise to build outcomes that weren't possible before.
Our strategic marketing team is a real example. Previously, they spent 30% of their time researching competitor strategies and market trends—gathering data, analyzing reports, sifting through survey results. Now, AI surfaces those insights in hours instead of weeks. They meet that intelligence with their actual expertise: understanding our customers' unique needs, identifying gaps competitors are missing, and building a strategy that moves the needle. Same team, same size, completely different output. They're not doing more work. They're doing better work.
These wins, where humans are elevated rather than removed, are the reason I stay.
My Strategic Compromise
I'm complicit in this. I have a seat at the table because I'm useful to the system. My influence is real, but it exists within a machine that's accelerating regardless of my choices.
I'm angry at the way the major players are pushing this technology forward regardless of the costs. There's real risk that the environmental damage will be catastrophic. Data centers are placed in underserved communities. Displacement at scale could lead to unprecedented struggle. I don't get to pretend I'm outside of that.
So, I'm trying to shape how it runs. Not to out-shout their efficiency gospel, but to outsmart it. The companies that figure this out first won't just be more ethical. They'll be more strategic, more creative, more agile. Their people will have careers, not just survival.
The future of work is being shaped right now, and there’s a closing window to influence what that looks like. So, I'm using my seat at the table to make sure this technology works for humans, not instead of them.
For more information on artificial intelligence and how it fits into your business, watch Impact's webinar, Lessons Learned from Incorporating AI into Business Processes.
