In an era of high customer demand for AI solutions, a lack of early traction is a critical warning sign. The combination of market pull and rapid development cycles means successful products should demonstrate momentum almost immediately. If it's not working fast, it's likely not working.

With hundreds of AI vendors pitching enterprises weekly, trust is low and differentiation is difficult. The most effective go-to-market strategy is to prove the technology works before asking for payment. Offering a free "solution sprint" for several weeks de-risks the decision for the customer and demonstrates confidence.

AI agent tools require significant training and iteration. Success depends less on software features and more on the vendor's commitment to implementation. Prioritize vendors offering a dedicated "forward-deployed engineer" who will actively help you train and deploy the agent.

Most buyers research and form an opinion before ever speaking to sales. Instead of making them wait for a demo, use on-site, AI-powered interactive demos to meet them where they are and capture high-intent leads.

When buying AI solutions, demand transparency from vendors about the specific models and prompts they use. Mollick argues that 'we use a prompt' is not a defensible 'secret sauce' and that this transparency is crucial for auditing results and ensuring you aren't paying for outdated or flawed technology.

Many enterprises explore AI due to pressure, not strategy, a phenomenon called "AI tourism." To avoid wasting resources on these tire-kickers, Sierra requires paid proofs-of-concept. The payment, even if modest, serves as a powerful filter for serious buyers with a real intent to deploy.

To cut through the hype, ask candidates to screen share during an interview and walk through their personal AI workflows. This provides an immediate, unfiltered view of their actual proficiency and whether they operate beyond simple chatbot usage.

The fastest way to understand AI's value is by using it for your actual work from day one, not by working through tutorials or sample projects. Applying AI to a genuine need, like analyzing your team's data or drafting a real memo, provides immediate, tangible feedback on its capabilities and limitations.

The success of your AI tool depends heavily on the vendor's human experts. Don't get stuck with a sales rep who doesn't understand the product. Demand access to their solution architects and onboarding specialists *before* you sign, ensuring you have a capable partner to guide your implementation.