The Real Growth Strategy for B2B AI? Security and Compliance

By Matt Blair

Enterprises love the promise of generative AI, but they also handle sensitive data and operate under strict regulations. When you’re selling AI‑powered products into the B2B market, the first question prospective customers will ask isn’t “What is the benchmark score of you model?” It’s “How will you protect our data and prove compliance?” Companies that treat security and governance as afterthoughts won’t get past procurement. Those that build trust into their products from day one will earn the right to grow in the B2B market.

B2B buyers are uneasy about AI purchases, as they should be

Surveys of chief information security officers show that legal and compliance hurdles are the biggest barrier to deploying AI. BigID’s AI Risk & Readiness report found that 64 % of organizations lack full visibility into their AI risks and nearly half have no AI‑specific security controls. More than half are unprepared for AI regulatory compliance. These gaps aren’t theoretical; they stop deals. A CISO quoted in The Hacker News explained that governance teams now routinely stall AI projects until vendors can answer detailed questions about data segregation, incident response, and regulatory certifications.

The problem isn’t just bureaucracy. AI has already produced real‑world leaks. A 2023 bug in an open‑source library exposed ChatGPT users’ chat history and payment information. Samsung banned ChatGPT internally after engineers pasted proprietary source code into the model, effectively leaking it. A study published this June found that OpenAI has been breached over 1,100 times, and half of the largest language‑model providers have experienced security incidents. When your tool handles customer data, a single breach can destroy trust and invite lawsuits.

Even OpenAI’s own CEO warns users not to assume confidentiality. Sam Altman recently told podcaster Theo Von that there is no legal privilege for ChatGPT conversations and that the company could be compelled to produce chat logs in court. He argued that AI chats should have the same privacy protections as conversations with doctors or lawyers, but admitted that the industry isn’t there yet. Altman’s comments don’t exactly inspire confidence from the very customers he’s asking to trust his tool with sensitive data, and they highlight how far the industry has to go before enterprise buyers will feel safe.

Building trust as a growth strategy

Companies selling AI products into regulated industries can’t ignore these realities. To win enterprise customers, they must show that security and compliance are built into the core of their offering. That means:

• Data safeguards from day one. Use encryption in transit and at rest, maintain strong tenant isolation, and guarantee that customer data will never be used to train the model without explicit consent.

• Demonstrable compliance. Map your controls to GDPR, CCPA, HIPAA and emerging laws like the EU AI Act. Obtain third‑party audits and be ready to share documentation.

• Transparent practices. Publish security and privacy notices that clearly explain who can access user data and under what circumstances. Respond quickly and openly to incidents.

• Cross‑functional governance. Establish a governance program that involves legal, security and business stakeholders early. Provide vendors and customers with standardized questionnaires and clear escalation paths.

Prioritizing these elements will slow your first release, but it will accelerate every enterprise deal thereafter. The organizations that adopt strong AI governance early gain efficiency and customer loyalty. Those that delay face increasing regulatory debt and lost opportunities.

Trust over raw power

In the consumer world, model size and benchmark scores drive headlines. In the B2B world, trust drives growth. Incremental improvements in model fluency mean nothing if a prospective client’s legal team refuses to approve the contract. With regulators tightening oversight and public awareness of privacy risks rising, companies that lead with security and compliance will win the market. When selling AI to other businesses, your most important feature isn’t a bigger or better model, it’s proof that you can be trusted.