AI at market speed, trust at enterprise scale.

It is an extraordinary moment to be building with AI. In just a few years, artificial intelligence has moved from experimental side projects to a central driver of business strategy. Boards are making AI a priority, and the market momentum is undeniable: the top 100 AI companies on Stripe reached $1 million in annualized revenue in a median of just 11.5 months, four months faster than the fastest-growing SaaS companies.

Executives across industries are investing aggressively to capture this potential. According to McKinsey, 92% of companies plan to increase their AI spend over the next three years — a clear signal that we are entering an era where AI will not just augment but fundamentally reshape industries.

Yet even in this moment of rapid acceleration, there is a parallel reality: moving fast is not enough. The organizations that succeed with AI will be those that unlock innovation without losing the anchor of credibility and trust.

From experiments to enterprise innovation

The early years of enterprise AI were defined by cautious proofs of concept and limited pilots. That stage has given way to something much more significant: enterprises are embedding AI into products, customer experiences, and operations at scale. The evidence is clear: AI patents grew nearly 30% globally in the past year (Stanford AI Index Report 2025), underscoring the extraordinary wave of innovation underway.

Experimentation and rapid iteration are not just industry-wide phenomena — they are core to how we build at Transcend as well. We have long believed in testing, shipping, and refining quickly, whether in creating integrations that unify fragmented data ecosystems or in pushing the boundaries of privacy automation. For example, Transcend’s platform leverages fine-tuned LLMs and NER (Named Entity Recognition) models to help identify and classify sensitive data across an organization, enabling enterprises to gain clarity and control over one of their most significant risks.

Market momentum meets market pressure

The momentum behind AI adoption is undeniable. Executives see AI as the key to competitive advantage, and investors expect companies to demonstrate not only strategy but tangible adoption. This collective force is pushing organizations forward, accelerating adoption cycles that once took years into timeframes measured in months.

But momentum alone does not guarantee success. The same energy that drives adoption can also create pressure to move too quickly, and to prioritize deployment before companies can address ethical questions and put governance frameworks in place.

The paradox at the center of AI

That pressure has created a paradox that could jeopardize a host of AI initiatives. While 92% of companies plan to increase AI investment in the next three years (McKinsey), 60% of AI initiatives will miss their value targets by 2027 due to fragmented and reactive governance (Gartner). The market is flooring the accelerator while enterprises stand on the brakes. This isn’t just a bottleneck; it’s the difference between leading an industry and being left behind.

The risks of moving too quickly

AI does deliver outsized opportunity, but the technology also carries real and immediate risks. Models that hallucinate or generate biased outcomes can undermine credibility. Mishandling sensitive data can create exposures that erode customer trust and invite regulatory scrutiny. And these failures are not theoretical.

• 95% of executives using AI report experiencing at least one AI-related mishap, while only 2% of organizations meet standards for responsible AI (Infosys, 2025).
• 65% of organizations say they already suffer from data bias, and more than a third report that bias has directly hurt their business (Cyber Magazine, 2025).
• McKinsey estimates $67 billion in global business losses in 2024 were linked to AI hallucinations, with nearly half of enterprise users making significant business decisions based on faulty outputs. (SecureITWorld, 2025)

The McKinsey 2025 survey of AI leaders underscores this reality, identifying governance and risk as the single greatest throttler of innovation out of six key blockers. Enterprises know the risks are real, but they currently lack the systems to manage them at scale.

And that is the paradox that will define this era: AI will always move faster than governance. Regulatory frameworks and internal policies cannot keep pace with the velocity of model development and deployment. Which means the defining enterprise question is no longer just “What can your AI do?” but “Do stakeholders (customers and procurement teams) believe your AI is safe to adopt?”

Enabling innovation at the speed of AI

At Transcend, we believe the answer is not to slow AI down, but to provide the infrastructure that enables innovation to move safely at market speed. This data layer should complement AI innovation, and together, determine whether AI will deliver real enterprise value.

That is why we provide the infrastructure for enterprises to adopt AI responsibly and at scale:

• Visibility into where and how AI is being used across vendors, teams, and customer touchpoints.
• Controls to safeguard sensitive data and prevent outputs that create ethical or legal liabilities.
• Compliance signals that meet enterprise procurement requirements and provide the evidence regulators demand.

The payoff is real. McKinsey finds that companies where the CEO directly oversees AI governance are significantly more likely to see outsized financial returns from generative AI deployments. This goes beyond mitigating risk and directly correlates with bottom-line value.

Enterprise-ready AI

The opportunity for AI is clear: it will reshape industries, redefine competitive advantage, and deliver outsized returns. But opportunity alone is not enough. With risks like bias, misuse, and data exposure rising — and traditional governance permanently lagging behind innovation — enterprises must prove that their AI is safe to adopt before it will scale.

This is the role Transcend plays. We deliver the visibility, controls, and compliance signals that prove an organization is enterprise-ready, helping ensure that AI is not seen as a liability but as a powerful accelerator of business growth.

The trajectory of AI adoption is unstoppable. The open question is not whether enterprises will embrace it, but how quickly and how safely they can scale. The winners will not be those who simply move the fastest, but those who inspire confidence and prove credibility at every step.

The era of AI is ours to shape. Let’s innovate boldly, but wisely.