Agentic AI Is The Next Frontier Of B2B Innovation

Daniel Saks is the CEO of Landbase, an intelligent go-to-market automation company, and cofounder of unicorn AppDirect.

Boom.

Do you remember the last time you used a technology that made your head go boom? Boom, as in, “This changes everything; things will never be the same, and we will use this technology forever?” Is that physical and intellectual feeling that you experience something magical, permanent, and life-changing?

I remember the times it’s happened to me. I recall the first time I used an Internet browser. The first time I held a smartphone with apps in my hands. And the first time I connected to the cloud. I’ve been a technologist and entrepreneur for nearly twenty years in Silicon Valley. Boom, I know, doesn’t happen all that often. But it’s happening now. The marvel this time? It’s agentic AI.

Agentic AI is an advanced form of artificial intelligence that acts autonomously, making decisions and performing tasks without constant human guidance. It actively works on behalf of businesses while continuously learning and adapting. This goes well beyond the capabilities of more familiar generative AI technology.

If you’ve never used it, you’ll experience a boom when you do. I’m convinced agentic AI will have a breakout moment in 2025—the kind that will reverberate for years to come. Here’s why.

The Agentic AI Moment

What’s happening now in agentic AI feels similar to the early days of cloud computing, when a small group of pioneering companies first recognized its transformative potential. I recognized this in 2009 when I first landed in San Francisco. Apple cofounder Steve Jobs had launched the App Store a few years earlier, and cloud computing was beginning to take shape. By my estimation, there were more than 30,000 independent software vendors (ISVs), but only 100 or so that could be considered truly cloud-native application companies. I marveled at how Salesforce and Workday led the charge and then at how Shopify, Cloudflare, and others followed. What started as a small base of standout cloud-native applications quickly grew into a movement that was to be felt worldwide.

The experience taught me to spot signals of transformative change. Unlike previous technological shifts, however, agentic AI grows stronger with each implementation and with each insight shared across the ecosystem. The pioneers who join this movement today won’t just be early adopters—they’ll be the architects of a new era in business technology.

Early innovations are emerging, pioneering companies are taking shape and the economic potential is staggering. McKinsey and Co. has estimated that generative AI alone could unlock $6.1 trillion to $7.9 trillion of value annually. For perspective, that’s larger than the GDPs of Japan and Italy, and nearly twice the size of the global auto industry. The estimated range of total economic potential of AI, which includes analytical AI, machine learning and deep learning, could be $15.5 trillion to $22.9 trillion annually by 2040, according to McKinsey.

Why Agentic AI Is The Future

Agentic AI represents a fundamental shift on several fronts. This includes how software serves business needs. These systems autonomously handle tasks, make decisions and continuously learn from their environment to optimize outcomes. While current generative AI tools augment human capabilities, agentic AI actively drives outcomes through automated decisions and actions based on dynamic inputs and goals.

Consider what this means for business operations. An agentic AI system can analyze sales data and actively pursue qualified leads. It can even engage prospects. It will anticipate bottlenecks in supply chains and automatically implement solutions before issues arise. It will also orchestrate entire marketing campaigns and adjust messaging and targeting as it learns what resonates with each audience segment.

In addition to its advanced functionality, the technology is also transforming how innovation is sold. The traditional per-seat software model is evolving towards outcomes-based models that reward actual value creation, not usage. It’s a radical departure that mirrors the very promise of agentic AI: technology that delivers results, not just features.

Finally, for all the fear of AI being a job killer, the reality is more nuanced. Consider: According to The World Economic Forum’s Future of Jobs Report 2025, the proportion of tasks completed by humans exclusively is expected to fall to 33% from 47% between 2025 and 2030. However, the percentage completed by humans assisted by technology is expected to rise to 33% from 30% as businesses improve collaboration between their humans, machines and algorithms. We’re creating unprecedented opportunities for teams to focus on what truly drives business value: strategy, relationships and innovation.

Building The Agentic AI Future

Which brings me back to “boom.” Booms can be messy, loud and disruptive. Agentic AI is prone to all of these.

The rise of agentic AI—AI systems capable of autonomous goal-setting, reasoning and action-taking—faces several challenges that span technological, economic, ethical and practical concerns. These include the following.

Agentic AI is tough to manage. Many AI “agents,” for example, struggle with context retention and fail to adapt in complex, open-ended environments. And, unlike traditional AI models, agentic systems are hard to measure since they don’t just generate outputs but interact over time.

Also, agentic AI systems don’t always place nicely with legacy systems that are not built for autonomy, adaptability or spontaneity.

AI agents can also develop and exhibit behaviors, discriminate unfairly or act in ways that are legally or ethically questionable. Cost is also a consideration. Agentic AI requires extensive training and investment. What is more, agentic AI requires human oversight, debugging and continuous fine-tuning to remain reliable.

But the investment is worthwhile. Recently, the research and analyst firm Gartner said agentic AI “will autonomously resolve 80% of common customer service issues without human intervention by 2029.” The savings that companies that deploy the technology will be immense. With these gains, the opportunity to invest in human capital will be staggering.

That’s a boom that should resonate with anyone who uses technology.

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