Unlike normal sales cycles where only 5-6% of prospects are actively buying, an AI super cycle forces all enterprises to seek solutions concurrently. This creates an unprecedented, time-sensitive window to capture budget if your product is perceived as an essential AI need.

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The current mass-adoption phase for AI tools means buying decisions that would normally take 5-7 years are being compressed into 1-2 years. Startups that don't secure customers now risk being shut out, as enterprises will lock in with their chosen vendors for the subsequent half-decade.

Buyers now use AI to arrive with a full research dossier on your product, pricing, and competitors. This changes the GTM role from persuading customers with clever messaging to enabling their decision-making. The new focus is helping buyers quickly experience your product's value on their own terms.

Companies like Notion and Datadog are re-accelerating by targeting new, dedicated AI budgets. This is separate from shrinking 'efficiency tool' budgets. Growth comes from solving problems that unlock this specific new spending category, not just adding a minor AI feature.

Unlike traditional B2B markets where only ~5% of customers are buying at any time, the AI boom has pushed nearly 100% of companies to seek solutions at once. This temporary gold rush warps perception of market size, creating a risk of over-investment similar to the COVID-era software bubble.

The massive TAM expansion for AI relies on shifting spend from labor to technology budgets. This shift won't happen because of top-down CIO mandates. It must be driven by bottom-up product pull, where the value proposition is so overwhelmingly clear that customers are compelled to adopt it.

Previous technology shifts like mobile or client-server were often pushed by technologists onto a hesitant market. In contrast, the current AI trend is being pulled by customers who are actively demanding AI features in their products, creating unprecedented pressure on companies to integrate them quickly.

G2's research shows a dramatic acceleration in AI adoption for B2B purchasing. The percentage of buyers starting their journey with an LLM surged from 29% to 50% in just four months. This signals a fundamental, non-negotiable shift in buyer behavior that marketing strategies must immediately address.

With buyers completing nearly 80% of their research using tools like Generative AI before vendor contact, the linear funnel is dead. Traditional metrics like MQLs and SQLs are meaningless. Go-to-market strategies must be rewritten to influence buyers during their independent, non-linear discovery phase.

AI is making buyer journeys non-linear and compressed. Instead of a linear funnel, GTM strategy must shift to a continuous, customer-centric "flywheel" model. Buyers conduct deep research upfront, making direct sales engagement optional for some and requiring an always-on, value-first approach.

A 'tale of two cities' exists in SaaS. Traditional software budgets are frozen, with spending eaten by price hikes from incumbents. Simultaneously, new, separate AI budgets are creating massive opportunities, making the market feel dead for classic SaaS but booming for AI-native solutions.