As organizations move beyond AI experimentation, the focus is shifting to results. Across industries, businesses are accelerating real AI value by pairing innovation with identity-first controls that make it possible to scale securely and responsibly.
At Success Academy, one of New York’s largest charter school networks, AI is already delivering measurable impact. The organization has established a dedicated AI team that assists teachers in designing more effective courses and instructional regimens, improving consistency and outcomes across classrooms. But as AI becomes embedded into daily workflows, new challenges emerge:
“Our job is to make sure we have the right people [who] can use this AI technology and that they're using it appropriately,” said Ken Abrams, Lead Systems Administrator at Success Academy Charter Schools.
Without proper safeguards, chatbots and automated agents could inadvertently expose or misuse information. For Success Academy, that challenge is magnified by scale: A small technology team supports thousands of staff members and tens of thousands of students. Like many organizations, the institution has found that deploying AI tools is no longer the hardest part — governing them is.
“We have to make sure: Are we sending this out correctly? Who is going to have access to this? When do they have access to this? When do we revoke access to this?” said Abrams.
That reality is pushing identity to the center of AI strategy. Traditionally, identity management tools have focused on verifying users, monitoring activity, and enforcing access controls across networks. Today, those same principles are being extended to AI agents, applications, and machine identities, helping to ensure that interactions are visible, auditable, and governed consistently.
This approach is taking shape through what’s known as an identity security fabric — a unified architecture designed for the AI era. By connecting every identity, whether human, machine, application, or AI agent, under a single framework, organizations gain the ability to monitor behavior, enforce policy, and maintain compliance without slowing innovation.
The value of identity-first AI strategies is also becoming clear in financial services, where trust and verification are critical. Equals Money, a UK-based fintech company, has accelerated its AI initiatives by using AI agents to automate repetitive tasks.
“The biggest problem for us in a financial services firm is always onboarding,” explained James Simcox, Chief Operations and Product Officer at Equals Money. “Are you who you say, or do you live where you live? Are you sanctioned? Is your company even real? … [verifying] those are really repetitive tasks. And so we've got agents who do that.”
As organizations build and deploy more AI agents, platforms are emerging to help standardize security from the start. Developers can use solutions like Auth0 for AI agents to embed security policies and authentication directly into the AI agents they build. This approach reduces the need for custom security coding and lowers long-term operational risk. Instead of worrying about whether systems are secure, teams can focus on building functionality, knowing that the appropriate guardrails are already in place.
As AI adoption accelerates, identity-first strategies are proving to be more than a security measure — they are becoming a business enabler. By making it possible to scale AI with confidence, identity controls are helping organizations turn AI potential into real-world results without compromising customer trust.
