AI Platform Cuts Enterprise Costs by 50%, Secures $10M

Imagine a world where enterprise workflows—those tedious, time-consuming tasks that keep HR, IT, legal, and finance departments up at night—are handled not by endless emails and ticket queues, but by AI agents that anticipate needs, process requests, and only bother humans for the truly complex stuff. That’s the vision behind ai.work, a Tel Aviv-based startup that’s just stepped out of stealth mode with a $10 million Seed funding round, led by former WalkMe executives Maor Ezer and Nir Nahum[1]. In a landscape where AI’s promise often outpaces real-world adoption, ai.work is taking a decidedly practical approach: targeting the internal processes that bog down companies, promising to cut enterprise operational costs by up to 50%[1].

Why This Matters Now

Let’s face it: 2025 is the year enterprise AI is finally supposed to deliver on its hype. According to WalkMe’s own research, AI spending at large organizations is projected to grow by 64% this year, jumping from $14 million to $23 million per company[4]. Yet, despite this surge in investment, many enterprises are struggling to translate AI ambitions into measurable results. Employees are overwhelmed by new tools, and the gap between what AI can theoretically do and what it actually delivers is wider than ever[4]. Enter ai.work, which is betting big on the idea that the real value of AI isn’t in flashy customer-facing features, but in quietly automating the behind-the-scenes grunt work that costs companies millions in inefficiency.

The Founders and Their Vision

Maor Ezer and Nir Nahum know a thing or two about enterprise pain points. Both held senior roles at WalkMe, the digital adoption platform now majority-owned by SAP. At WalkMe, they saw firsthand how companies struggled to get employees to adopt new technologies—and how much friction existed in internal processes. Their new venture, ai.work, is designed to address these challenges head-on.

“Our goal is to make internal operations as seamless as possible,” Ezer explained in a recent interview. “We’re not trying to replace humans; we’re giving them superpowers by automating the repetitive stuff so they can focus on what really matters.”[1]

What ai.work Actually Does

ai.work’s platform, dubbed “AI Worker,” is built to integrate with enterprise mainstays like ServiceNow, Slack, Salesforce, and Microsoft 365. The idea is simple: deploy AI-driven agents that handle routine requests across IT, legal, HR, procurement, and finance. These agents process tickets, fill out forms, and only escalate exceptions to human managers. The result? Faster resolution times, fewer errors, and—crucially—a significant reduction in operational costs.

For example, imagine an employee needs IT support. Instead of submitting a ticket and waiting for a response, the AI agent can diagnose the issue, suggest solutions, and even implement fixes—all without human intervention. If the problem is too complex, it’s routed to the right person, but most of the time, the AI handles it seamlessly[1].

The Broader Context: Enterprise AI in 2025

The launch of ai.work comes at a pivotal moment for enterprise AI. According to WalkMe’s 2025 State of Digital Adoption report, more than 3,700 global leaders and employees are grappling with the challenges of integrating AI into their workflows[2]. While customer service and creative tasks have received much of the attention, the real bottleneck is often internal operations. Manual processes, outdated systems, and a lack of digital adoption are costing companies millions in lost productivity[2][4].

Interestingly enough, the gap between AI ambitions and employee readiness is a recurring theme. Many organizations are investing heavily in AI, but few have the infrastructure or culture to make it stick. ai.work’s approach—focusing on integration with existing systems and automating routine tasks—is a pragmatic response to this challenge[4].

Real-World Applications and Impact

Let’s look at some real-world scenarios. In HR, ai.work’s AI agents can automate onboarding, offboarding, and benefits administration. In IT, they can handle password resets, software installations, and basic troubleshooting. In legal and procurement, they can manage contract reviews and purchase order processing. The potential for cost savings is enormous: by automating these tasks, companies can reduce the need for large support teams and free up staff for higher-value work.

One early adopter, a mid-sized tech firm, reported a 50% reduction in IT support costs after deploying ai.work’s platform. “We’re seeing faster resolution times, happier employees, and a significant drop in operational overhead,” the company’s CIO said[1].

Funding and Market Interest

ai.work’s $10 million Seed round was led by A* and lool ventures, with participation from First Minute Capital, SV Angel, and Liquid2, among others[1]. The strong investor interest reflects a broader trend: venture capital is pouring into enterprise AI startups that promise tangible, measurable ROI. In a market crowded with hype, ai.work stands out for its focus on real-world problems and proven founders.

Historical Context: The Evolution of Enterprise Automation

To appreciate what ai.work is doing, it’s worth looking back at the evolution of enterprise automation. The first wave was about digitizing paper processes. The second wave introduced workflow automation tools like ServiceNow and Salesforce. The third wave—where we are now—is about embedding intelligence into these workflows, so they can adapt and learn.

ai.work is part of this third wave, but it’s also pushing the envelope by making AI agents truly autonomous. Unlike earlier solutions that required extensive configuration and manual oversight, ai.work’s platform is designed to learn from interactions and improve over time[1].

Future Implications and Potential Outcomes

Looking ahead, the implications are profound. If ai.work and similar platforms succeed, we could see a fundamental shift in how enterprises operate. Internal operations could become more agile, responsive, and cost-effective. Employees would spend less time on routine tasks and more time on strategic initiatives. And companies that embrace this new model could gain a significant competitive edge.

Of course, there are challenges. Security, privacy, and change management are all critical considerations. But as someone who’s followed AI for years, I’m thinking that the companies that get this right will be the ones that thrive in the next decade.

Different Perspectives and Approaches

Not everyone is convinced that AI-driven automation is the silver bullet. Some critics argue that over-reliance on AI could lead to job losses or a loss of institutional knowledge. Others worry about the “black box” nature of AI decision-making. But ai.work’s approach—focusing on routine, rules-based tasks and leaving complex decisions to humans—is a pragmatic middle ground.

There’s also the question of integration. Many companies have invested heavily in legacy systems, and getting AI to play nice with these can be a challenge. ai.work’s focus on compatibility with major platforms is a smart move, but it’s not without its hurdles.

Comparison Table: ai.work vs. Traditional Enterprise Automation

The Human Touch: Why This Matters to Me

As someone who’s spent years covering enterprise technology, I’ve seen my fair share of “next big things.” But ai.work feels different. It’s not just about technology for technology’s sake—it’s about solving real problems that affect real people. I’ve talked to enough overworked IT and HR professionals to know that anything that can take some of the load off is going to be welcome.

Conclusion: The Road Ahead

ai.work’s emergence is a sign of things to come. As enterprises grapple with the challenges of digital transformation, platforms that can automate routine internal processes will be in high demand. The $10 million Seed round is just the beginning. If ai.work can deliver on its promise—and early signs are promising—it could help redefine how companies operate, making them more efficient, agile, and human-centric.

In the end, the real winners won’t just be the companies that adopt these technologies, but the employees who get to focus on more meaningful work. And that, to me, is what enterprise AI should be all about.

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