Who Else Is in This Space?

AI is everywhere in 2026. Founders hear stories of small teams using chatbots to automate sales, content, and data science. But once the initial excitement fades, a more practical problem shows up.

It is in every founder's conversations. After the first ethics and compliance questions are answered, two follow-ups always come up.

Who else is in this space?

What certifications do we actually need?

These are practical questions. They come up when budgets are approved, when sales teams prepare enterprise calls, and when founders try to decide whether they are building something differentiated or just another variation of the same promise.

This article focuses on that moment. Not the why of regulation, but the how of navigating a crowded market while preparing for the rules that now shape it. The goal is simple: clearer decisions, fewer surprises, and faster progress.

Why These Questions Keep Coming Up

Before any framework helps, it is worth acknowledging the doubt behind these questions.

I know what you’re thinking.

Most AI products look the same.

Founders see all kinds of tools claiming to offer AI agents, yet many are little more than scripted workflows. As echoed in 2025 Reddit discussions (e.g., in r/AI_Agents), many question: "Has anyone actually built real AI agents, or is this just automation with a new label?"

That skepticism is reasonable.

At the same time, the market feels crowded. When everyone claims to solve the same problem, it becomes hard to see where real differentiation lives. Founders do not want to copy what already exists. They want to understand where the gaps are and whether those gaps are worth pursuing.

Then there is regulation. New rules like the EU AI Act signal the end of dealing with compliance later. Yet most teams are unsure what applies to them. GDPR. ISO standards. AI-specific frameworks. The list feels long, and the order unclear.

These concerns are connected, but they do not carry equal weight at every stage. Once founders accept that regulation is inevitable, the real challenge becomes sequencing. Which rules matter now. Which competitors actually threaten your position. And where structure saves time instead of slowing you down.

That is why regulatory readiness is not a side issue. It is the starting point for understanding your real market.

Why Regulatory Readiness Often Comes First

Understanding the rules early helps clarify the market you're entering, though priorities may vary by region and stage.

The EU AI Act is the first broad legal framework designed specifically for artificial intelligence (EU AI Act, effective phases through 2026-2027). It follows a risk-based approach. The higher the potential impact of a system on people’s rights or safety, the more obligations apply.

Some uses are banned outright. Others fall into a high-risk category, such as AI used in hiring, credit scoring, or safety-critical systems. High-risk systems require structured risk assessments, clear documentation, strong data governance, and human oversight.

Even lower-risk systems are not an exception. Transparency matters. Users must understand when AI is involved and what it does.

This changes how AI products are built.

While the EU AI Act sets a global benchmark, 2026 brings significant US developments. States like California, Texas, New York, and Colorado have enacted laws effective from January 1 (with Colorado delayed to February or June for some provisions). California's AI Safety Act requires developers of high-risk models to disclose risk mitigation plans and report safety incidents, while Texas's Responsible Artificial Intelligence Governance Act emphasizes consumer protections through governance frameworks. New York's RAISE Act mandates similar transparency for automated decision-making tools. 

However, the US federal Executive Order from December 2025 aims to challenge taxing state laws, promoting a 'lightly burdensome' national approach: founders should monitor potential takeovers or lawsuits via the new AI Litigation Task Force.

Standards help translate legal language into operational structure. ISO 42001, the first AI management system standard, gives teams a way to define policies for data use, monitoring, accountability, and risk management . It does not turn teams into lawyers. It gives them a shared operating model.

ISO 27001 and ISO 27701 serve a similar purpose for security and privacy. ISO 27001 establishes how information is protected. ISO 27701 extends that foundation to personal data and privacy responsibilities. Together, they show that access control, encryption, and incident handling are designed in, not added later. These US rules align well with ISO 42001 for risk management and ISO 27701 for privacy, offering a cross-jurisdictional foundation.

This is what you should know.

You do not need every certificate.

You need the ones your customers expect.

Early compliance work is not wasted effort. It reduces sales friction later. Enterprise buyers ask these questions early, often before a product demo. Clear answers build confidence long before a contract discussion.

How to See Who You’re Really Competing With

Once the regulatory baseline is clear, competitive analysis becomes more useful.

Many founders make the same mistake. They compare feature lists.

That approach misses the point.

A meaningful competitive analysis focuses on outcomes, positioning, and trade-offs. Not checkboxes.

Start by defining the problem you solve and the people you solve it for. An AI agent for e-commerce support does not compete with a data science platform for banks, even if both rely on similar models.

Next, map the real alternatives. That includes direct competitors, open-source tools, internal scripts, and manual processes. For many teams, the biggest competitor is not another startup. It is doing nothing and living with inefficiency.

Then look at how each option delivers value. Speed. Cost. Reliability. Integration effort. Ongoing maintenance. Switching costs. These are the dimensions buyers actually care about.

Simple visual tools help. A positioning map, such as price versus depth of functionality, often reveals gaps. Sometimes the opportunity is not better technology, but clearer scope or calmer execution.

This is also where honesty matters.

List your weaknesses. Be explicit about what you do not do well yet. It is uncomfortable, but it prevents surprises later and sharpens the roadmap.

Competitive analysis is not a one-time exercise. Markets move. Update it regularly, or decisions will drift away from reality.

Turning Insight Into Action

Competitive clarity and regulatory readiness only matter if they shape what you build next.

This is where many strategy documents stop. We focus on implementation.

Firms like Camsol, an IT services company focused on AI agents and compliance, exemplify how external partners can help. They provide steady engineering support for production systems in areas like lead qualification, competitor monitoring, user support, and data cleaning. Not demos. Production systems with measurable outcomes.

Security and compliance are part of the foundation. End-to-end encryption. Zero-trust access. Automated vulnerability scans. EU-hosted infrastructure. These choices support alignment with standards like ISO 27001 and ISO 42001 from the start.

Such providers often offer regulatory readiness assessments and competitive analysis workshops. Not slide decks that gather dust. Working sessions that lead to clear decisions and concrete next steps. While partnering with specialists can accelerate progress, founders should evaluate multiple options to ensure alignment with their specific needs.

Who else is in this space and what certifications are needed are not time wasters. They are signs that a product is moving from idea to reality.

AI products outlive hype cycles. They face scrutiny from users, buyers, and regulators. The teams that succeed are the ones who understand the rules, know their real competitors, and build with intention.

Agents should solve real problems.

Compliance should create trust.

Differentiation should be clear.