An AI-enabled chat application can answer questions and make suggestions. Agentic AI, however, can do so much more. The new frontier in artificial intelligence, AI agents don’t just react to user inputs. They go beyond by proactively pursuing tasks and finding new solutions. They can learn, reason and act — much like humans do.
“Agentic AI is taking action based on data, and it will be incredibly transformative to businesses,” said Daniel Saks, CEO of Landbase, a marketing company that uses AI agents to automate clients’ routine marketing tasks, including everything from website visitor intelligence to content creation to reporting and analytics.
Because of its “transformative” potential, the market for agentic AI is expected to swell from $78.4 billion in 2025 to over $56 billion by 2030, according to MarketsAndMarkets.
To help their company claim its piece of that enormous pie, Saks said senior leaders must prioritize three goals above all others: collecting unique data, investing in flexible IT infrastructure and leading people by way of effective change management.
Understanding AI Agent Applications in Business
Landbase uses agentic AI to help clients generate leads, execute outbound sales and implement marketing campaigns.
“We have three value propositions: to be faster, cheaper and better,” Saks said.
“Faster means we can run campaigns … in minutes, not months. Cheaper means you don’t need expensive software, data and a lot of humans. Better means we can execute campaigns with four to seven times better performance [compared to a conventional approach].”
Agentic AI is key to speeding processes and reducing human labor. “In our world, if you want someone to send an outbound sales campaign, they need to first understand who they’re targeting,” continued Saks.
He said companies then have to understand how to acquire prospects’ contact information and how to construct the perfect message that will catch their attention. “Essentially, all of these different steps can be captured by AI agents.”
The result is streamlined processes. It frees human workers to focus their efforts on value-added contributions instead of rote and routine tasks.
And it’s not just sales and marketing that can benefit. Businesses in a range of other industries can reap the same rewards. In healthcare, for example, AI agents could help alleviate physician shortages by automating and augmenting diagnostics and other time-consuming, automate-able tasks. Or take the IT industry, where software engineers traditionally have had to write hundreds of lines of code.
“With a coding agentic AI application, a lot of that work can be done for you,” Saks said.
Need to write up a contract? “Agentic AI can draft it,” Saks continued. “And while you still have to review it, you are free to spend a lot more time on strategy, versus sitting in front of a computer reading and red-lining.”
Based on his own firm’s experience with it, Saks said companies looking to leverage agentic AI should focus on three things in order to be successful:
Unique Data
High-quality data is the foundation of all AI, of course. But in order to be a competitive differentiator, agentic AI requires something more. Specifically, business leaders need to power their AI agents with data that is niche, novel and hard to find, according to Saks. “If you want an AI agent to be better than a human agent or to do things that humans can’t do, you need to feed it with very unique data — not just about your role or your company, but also data around wisdom of the crowds,” he said.
That means going deeper than what is publicly available. If you’re a commercial construction company looking to bid on a project, for example, go to City Hall and get the paper blueprints, then digitize them and train the AI agents on that. Such “non-public, non-digitized signals” can generate the unique outputs that give businesses a competitive edge.
“If they’re not available on the public internet, then the first person to digitize them is going to have a huge advantage,” Saks said.
Cloud-Based Infrastructure
Along with bespoke data, technological infrastructure plays a key role in the successful implementation of AI agents, according to Saks. Companies will likely access agentic AI through industry-specific applications, and those applications will need a robust platform on which to run, he pointed out.
“With agentic AI, there’s more compute being used, and all that needs to happen somewhere,” explained Saks, who said demand for AI agents will drive the need for more compute power. “And from an infrastructure perspective, that means that cloud is really critical.”
Change Management
People also come into play. After all, agentic AI represents a new way of operating. Business leaders will therefore need to factor in the impact on staff.
“It requires a lot of change management,” noted Saks, who said senior leaders need to encourage everyone in their organization to adopt the right tools. “At Landbase, our three values are: Own it, automate it and elevate it. That speaks to the notion of adopting tools to make everyone more efficient in their role.”
As with any AI-driven effort, it’s important in the early days to keep humans in the loop, according to Saks, who once tried using agentic AI to automate conversations on LinkedIn, hoping to efficiently increase his social media presence. Unfortunately, it backfired. “Within 24 hours it had responded to people in languages that I don’t even understand. It used tones that were inappropriate. It responded about things that I don’t even know about,” he said.
His point? Proceed with caution. But by all means, do proceed. “AI is coming for your job. It’s coming for the job of every salesperson, lawyer and, frankly, CEO,” he said, adding that individuals at every level of every business must work to prove their value in an agentic-AI world.
“The human element will be the differentiator,” continued Saks, who said humans at the very bottom of the organization and at the very top can differentiate themselves by focusing on creativity, relationships and offline perspectives. “You need to push your people to harness machine intelligence to make better decisions. And at the same time, you need to train your people in decision making and creativity. That’s the durable skillset that AI will never be able to take on.”
Adam Stone is a journalist with more than 20 years of experience covering technology trends in the public and private sectors.
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