How to Find Out What AI Your Competitors Are Using

You noticed something. Their proposals come back faster. Their team looks leaner than it used to be. Their content output doubled without any new hires. You do not have proof yet, but the signs are there: your competitors are using AI, and you are not sure to what extent.

This is worth taking seriously. The gap between a company using AI well and one that is not grows every month. It is not a one-time advantage. It compounds.

Why the Gap Compounds

Every week a competitor uses AI to speed up their proposal process, they are getting faster at winning deals. Every week they use AI to accelerate research and report delivery, their clients are getting more value per dollar spent. The operational advantages stack. By the time the gap becomes obvious, it has already been building for months.

This is why AI competitive intelligence is worth the effort. The sooner you know what they are doing, the sooner you can decide how to respond. Not to copy them, but to find where they have gaps and where you have an opening.

What Public Signals Tell You

You do not need insider access to understand what your competitors are doing with AI. Most of what you need is already public.

Job postings

This is the most reliable signal. When a company posts for an "AI Engineer," a "Prompt Engineer," or an "Automation Specialist," they are telling you exactly where they are investing. When they post for a "Head of AI Operations" or "AI Implementation Lead," they are building organizational capacity, not experimenting.

Look at the specific tools and platforms listed in job requirements. If they are consistently asking for experience with a specific AI platform, that tells you what they are running in production. Save these postings. Track them over time. Changes in what they hire for signal shifts in their strategy.

Product pages and feature announcements

If your competitors are product companies, their public changelogs and feature announcements are a direct window into what they have built. Even if they are not flagging it as "AI," look for anything described as automated, instant, or AI-assisted. That language usually means something that was previously manual is now handled by a model.

If they are service companies, look at their pricing pages and service descriptions. Have new offerings appeared? Have they started advertising faster turnaround times than they used to? Those are signals worth tracking.

LinkedIn activity from their team

People talk. Their team members post about tools they are using, workflows they have built, and problems they have solved. A VP of Operations posting about automating their reporting process is useful intelligence. A consultant sharing a template they built with an AI tool tells you something about what they are deploying with clients.

Follow key people at your top competitors on LinkedIn. Not obsessively, but consistently. What they share reflects what they are working on.

Tech stack signals

Tools like BuiltWith and SimilarTech show what technologies a website is running. For web-facing AI applications, this gives you a partial picture of their stack. Job descriptions often fill in the rest, since companies list the specific tools they want candidates to know.

This will not give you a complete picture, but it will give you enough to form a hypothesis about what category of AI they are investing in.

What to Do With the Information

The wrong response to competitive intelligence is to copy what they are doing. By the time you have finished building what they built six months ago, they are six months further ahead.

The right response is to look for the gaps. What are they doing well? What are they not doing? Where does their AI investment appear to stop? Those gaps are where you build your advantage.

If they are using AI to speed up delivery but not to improve quality or customization, that is your opening. If they are automating routine work but leaving complex client work entirely manual, that is where you differentiate.

Use the intelligence to make a decision about where to focus, not to replicate what already exists.

How to Do This Systematically

Ad hoc competitive research does not work. You check once, form an opinion, and never revisit it. The information goes stale fast.

Set up Google Alerts for your top five competitors plus their key executive names. When something gets published, you will see it. Assign one person on your team to do a monthly sweep: job postings, LinkedIn, product updates, any press. It takes about an hour a month per competitor.

Build a one-page competitive AI map. For each competitor: what they appear to be using, what it tells you about their priorities, and where you see gaps. Update it monthly. Over time, you will see patterns and trajectories, not just snapshots.

When to Get Outside Help

If you are running a real operation, a monthly competitive scan is probably the limit of what you will consistently execute. Deeper analysis takes more time and more expertise than most teams have available.

A proper AI competitive audit goes further: structured job posting analysis across multiple competitors, technical stack research, product intelligence, and a synthesis of what the combined picture tells you about where the industry is heading and where you have the clearest opportunity to lead.

If you want that level of analysis without pulling your own team off their core work, that is what we do.

Learn more about our AI competitive audit and what it delivers.