After a decade of tracking emerging technologies, I’ve developed a simple framework for evaluation. Six questions that cut through the hype and help identify what’s real.

I apply these to everything - AI capabilities, quantum computing claims, biotech breakthroughs, whatever. They’re not perfect, but they’ve kept me from some expensive mistakes.

Question 1: What Can It Do Today?

Not what it might do in five years. Not what the roadmap promises. What can it actually do right now, in production, at scale?

This question immediately separates technologies that are real from those that are merely promising. It forces you to look past the demo and find actual deployments.

For AI agents, the honest answer in 2025 is: handle well-defined tasks in constrained domains with appropriate human oversight. Not: autonomously run complex processes without supervision.

For quantum computing: solve certain specialized problems faster than classical computers in laboratory settings. Not: break encryption or revolutionize drug discovery.

Many technologies fail this question - they’re real in labs but not in production. That’s not disqualifying, but it resets your timeline expectations.

How to apply it: Ask for production examples. Ask for customer references. Ask for performance metrics from real deployments. Be skeptical of “we’ll have that next quarter” answers.

Question 2: What Would Have to Change for Mass Adoption?

Most emerging technologies face barriers to widespread use. Understanding those barriers tells you what to watch for.

The barriers typically fall into categories:

Cost: The technology works but is too expensive for most applications. What would have to change for costs to drop 10x?

Performance: The technology works but not reliably or quickly enough. What improvements are needed?

Infrastructure: The technology works but requires supporting systems that don’t exist yet. What infrastructure has to be built?

Regulation: The technology works but can’t be legally deployed. What regulatory changes are needed?

Behavior: The technology works but requires people to change how they work or live. How realistic is that behavior change?

Ecosystem: The technology works but needs complementary products or services. Who else needs to build what?

For each barrier, assess how likely it is to be overcome and on what timeline. This gives you a more realistic adoption trajectory than vendor promises.

How to apply it: List every barrier you can identify. For each, specify what would have to change and how likely that change is.

Question 3: Who’s Actually Paying?

Follow the money. Someone buying a technology is much stronger evidence than someone investing in it or talking about it.

This question distinguishes technologies with product-market fit from those that are interesting but not useful enough to buy. It also reveals which use cases are genuinely valuable.

For any emerging technology, ask: Who is paying real money for this today? How much are they paying? Is their spending increasing?

If the answer is “mostly grant funding” or “mostly venture capital” or “mostly pilot programs,” the technology isn’t proven yet. If actual customers are paying real money that they’d otherwise spend elsewhere, something is working.

How to apply it: Find the actual revenue (or meaningful commercial contracts). Don’t count investment, grants, or partnership announcements - count paying customers.

Question 4: What’s the Incumbent Response?

Emerging technologies that threaten incumbents will face resistance. Understanding that resistance helps you predict how adoption will actually unfold.

Incumbents can respond in several ways:

Ignore: Happens when the technology seems irrelevant or too early. This creates opportunity windows.

Adopt: Incumbents incorporate the technology themselves. This validates the technology but reduces opportunities for new entrants.

Acquire: Incumbents buy the emerging companies. Good for startups, changes the competitive dynamics.

Block: Through regulation, standards, IP, or market power. This slows adoption regardless of technology merit.

Discredit: Attacking the technology’s reliability, safety, or ethics. Sometimes legitimate, sometimes defensive.

For any emerging technology, map who the incumbents are and how they’re likely to respond. This affects both timelines and the nature of opportunities.

How to apply it: Identify who loses if this technology succeeds. What resources do they have to respond? What response seems likely? How does that affect the adoption path?

Question 5: What’s the Adoption Pattern?

Different technologies spread in different ways. Understanding the pattern helps you predict trajectories and identify entry points.

Some common patterns:

Infrastructure first: The technology enables other things but isn’t valuable alone. Value comes from applications built on top. Example: cloud computing.

High-end first: The technology starts expensive and serves high-value applications, then moves down-market. Example: genome sequencing.

Consumer to enterprise: Consumer adoption creates awareness and expectations that drive enterprise adoption. Example: smartphones.

Enterprise to consumer: Enterprise deployment proves reliability and reduces costs, enabling consumer applications. Example: GPS.

Niche dominance: The technology works extremely well for a narrow application before expanding. Example: GPUs for gaming before AI.

For any emerging technology, ask what adoption pattern makes sense and what stage we’re at.

How to apply it: Look at historical analogies. What other technologies followed similar patterns? Where did opportunities emerge in those cases?

Question 6: What’s My Specific Angle?

This is the most important question and the one most often skipped.

Even if a technology is genuinely promising, you need a specific way to capture value from it. “AI is big” doesn’t tell you what to do.

Questions to ask yourself:

What unique position do I have? Do you have data, distribution, expertise, or relationships that others don’t? Can you apply this technology in ways others can’t?

What’s my time horizon? Are you trying to capture value in 1 year, 5 years, or 10 years? Different opportunities suit different horizons.

What’s my risk tolerance? Early-stage technology bets can fail. Can you afford the downside if this doesn’t pan out?

What’s my commitment level? Are you willing to make this a major focus, or is it exploratory? Major bets require major commitment.

What would have to be true? For this opportunity to work out, what has to happen? How likely is that?

Most people tracking emerging technology never get specific about their own position. They accumulate knowledge without strategy. This question forces specificity.

How to apply it: Write down your specific thesis. What will you do, why are you positioned to do it, and what has to be true for it to succeed?

Using the Framework

I apply these six questions to every emerging technology I evaluate:

1. What can it do today?
2. What would have to change for mass adoption?
3. Who’s actually paying?
4. What’s the incumbent response?
5. What’s the adoption pattern?
6. What’s my specific angle?

The first five are about understanding reality. The sixth is about acting on it.

No framework is perfect. Unexpected breakthroughs happen. Predictions fail. But systematic evaluation beats hype-driven enthusiasm every time.

The next time you encounter an exciting emerging technology, run it through these questions before making any commitments. You’ll either validate your enthusiasm with evidence, or save yourself from an expensive mistake.