Agentic AI is a Force Multiplier for the Best Employees

Like it or not, your staff are already using AI.

Walk around any modern office, and you’ll likely see Copilot or ChatGPT tucked behind a spreadsheet, an AI summarizer pulling key takeaways from a meeting transcript, or an AI-powered scheduling app organizing a calendar.

Pretending otherwise is naïve.

It’s normal – and, frankly, prudent – to be at least a little concerned about AI use. But that doesn’t mean you can write it off altogether. AI can make the best employees faster and more efficient. It can be a force multiplier for human talent.

And, increasingly, that means not just simply assistants, but agentic AI systems that don’t just answer questions but act autonomously.

The question for leadership isn’t whether staff should use AI; it’s whether they’re using it safely.

How and Why Agentic AI is Reshaping Everyday Work

Agentic AI is the next evolution of the AI tools we’re all already familiar with.

Rather than just generating answers or summaries, these systems can scan multiple data sources, decide on the best action, and even trigger workflows without constant human direction.

In many ways, they’re more of a digital colleague than a mere tool – that’s why your top performers use them as a way to amplify their own effectiveness. For example:

• An analyst can cut down hours of report review to just a few minutes.
• A sales rep can let an AI agent book meetings and qualify leads while they focus on closing deals.
• A security analyst can offload routine log triage so they can commit more time and energy to closing down real threats.

However, until recently, deploying AI agents required heavy infrastructure, custom pipelines, and constant babysitting. Put simply, agentic AI was out of reach for almost all organizations.

But that has changed.

Advances like retrieval-augmented generation (RAG), open frameworks such as LangChain, and cloud-native orchestration have stripped away complexity, making agentic AI an everyday operational reality.

In fact, if you look hard enough, you can find AI agents in almost every facet of business.

Where Agentic AI is Already Changing Work

AI agents currently sit at the “peak of inflated expectations” on Gartner’s Hype Cycle for AI. That means two things: there’s significant public interest, but there are some unrealistic expectations about what the technology can and will be able to do.

So, let’s keep this grounded. Here’s where agentic AI is actually having an impact.

Customer Experience

Chances are, you’ve already interacted with a customer service agent. They can handle routine queries around the clock and escalate the toughest problems to human staff.

That means customer-facing teams spend less time on repetitive tasks and more time solving issues that really require judgment. Research from Morgan Stanley predicts retail could save $6B through agentic AI efficiencies.

Sales and Marketing

Coaching agents can analyze CRM data, run practice role-plays with sales reps, and give feedback to improve win rates. Others engage inbound leads automatically, handle objections, and schedule meetings. As a result, salespeople spend less energy on admin and more time actually selling.

Healthcare

Agents can review large amounts of clinical data, automate paperwork like notetaking, and even help triage patients in emergency rooms. This means doctors and nurses gain back time for patient care instead of chasing paperwork.

Banking and Financial Services

Fraud detection agents monitor transactions in real time and stop suspicious activity.

Human Resources

Agents can screen resumes, set up interviews, and help HR teams understand employee feedback. They can also recommend training, track compliance, and simplify onboarding and benefits management. This frees HR leaders to spend more time on high-value employee care, strategy, and retention initiatives.

Security Operations

SecOps agents can filter alerts, enrich threat intelligence, and suggest response actions. By clearing the noise, they give analysts more time to chase real intrusions.

Agentic AI’s appeal is obvious. But its benefits come with trade-offs, from security and compliance risks to integration challenges, cost overruns, and reliability issues. The same autonomy that makes agentic AI powerful also makes it dangerous without the right guardrails.

Power Comes with a Price…

Agentic AI promises faster workflows, sharper insights, and a lighter load on your best people. But those gains don’t come free. Integrating agents into legacy systems can be messy, costs can spiral when projects don’t deliver ROI, and even the most advanced models can still make mistakes or hallucinate.

On top of that, these systems often need access to critical systems and sensitive data, which poses serious security and compliance risks – especially considering AI agents work autonomously.

These risks can stack up. A shaky integration undermines reliability, unreliable output inflates costs, and weak governance turns efficiency into exposure. And when that happens, the very employees you want to empower with AI end up slowed down by fixing or second-guessing its mistakes.

What’s more, wasted investment is a real possibility. Gartner predicts that over 40% of agentic AI projects will be cancelled by the end of 2027.

Organizations that move forward without clear pilots and strong guardrails will struggle. Those that adopt agentic AI with discipline (testing first, enforcing oversight, and treating agents like trusted but fallible colleagues) will capture the upside without letting the technology get out of control.

…But Standing Still is the Bigger Risk

The risks of using agentic AI are great.

But the costs of not using agentic AI could be even greater.

Relying on legacy systems and manual workflows already carries risks of inefficiency, burnout, and competitive decline. They’re slower, harder to secure, and force employees to waste hours on repetitive tasks.

In security specifically, attackers are already using AI to scale and speed up their operations. If defenders stick with manual workflows, they’re fighting machine-speed threats with human-speed tools.

Investing in and adopting AI isn’t a choice between safe old tools and risky new ones. It’s a choice between managing the risk of modernization and accepting the risks of stagnation. If your employees aren’t learning to use AI effectively, they’re falling behind peers who are. And if your organization refuses to modernize, you’re ceding ground to competitors who already realize the benefits AI brings.

Your staff know this. It’s why they’re already experimenting with AI tools on their own. They want to work faster, learn new skills, and avoid wasting time on repetitive, low-value tasks.

Ignoring that reality doesn’t eliminate the risk – it just drives AI use underground, where it’s harder to monitor and control.

What Does This Mean for Your Business?

Employees are going to use AI; it’s leadership’s responsibility to ensure they do it safely.

Organizations that invest in training and upskilling give their people the knowledge to use AI responsibly and effectively. Those that don’t leave employees to develop ad hoc habits that may be inefficient, insecure, or non-compliant.

The same is true for retention. Ambitious employees want to stay ahead, and they want to work with modern tools. If you block AI, they’ll either find risky workarounds or leave for companies that don’t, and those are usually your highest performers – the very people AI helps the most.

And, finally, efficiency. Teams that embrace AI with guardrails will deliver more, faster. Teams that cling to outdated workflows will be left behind – not because they lack talent, but because they lack the tools to compete.