Discover how leading companies are operationalizing agentic AI to transform their business processes and gain competitive advantage
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321 South Dixie HighwayBusiness leaders don't need more AI hype. They need clarity on what's real, what's working, and what it means for their teams and bottom line. Agentic AI — systems capable of independently planning, reasoning, and executing tasks across entire workflows — has quietly moved from experimental to essential. And while many organizations are still in the "what could we do with AI?" phase, the companies gaining competitive ground have already shifted into deployment.
Agentic AI isn't replacing jobs in broad strokes — it's transforming how work gets done, augmenting talent, accelerating outcomes, and dramatically reducing inefficiencies across critical processes.
Here's how forward-thinking companies are doing more than just exploring AI — they're operationalizing it.
LinkedIn recently launched its AI Hiring Assistant, one of the clearest examples of agentic AI built into a core business process. The assistant autonomously handles key steps in recruitment:
This isn't just automation — it's intelligent delegation.
Hari Srinivasan, VP of Product at LinkedIn, summed it up well: the goal is to "help recruiters be recruiters again." By offloading the repetitive and mechanical tasks, talent teams can focus on what they do best — human connection, evaluation, and strategy.
Shopify's approach is more than just encouraging AI adoption — it's requiring it. CEO Tobi Lütke issued a directive: before any team can request headcount or additional resources, they must demonstrate why AI can't handle the task.
AI capability is now part of Shopify's performance review criteria. In other words, using AI effectively isn't just encouraged — it's a core skill expectation. That level of integration is where the future of work is heading.
For companies wondering how to "get buy-in" for AI, Shopify's example is a reset. The expectation isn't that AI fits into the current process — it's that processes should evolve around what AI can do.
Cielo, a global talent acquisition partner, introduced an agentic AI platform that learns from past performance and autonomously executes elements of the hiring lifecycle. This includes:
Matt Jones, Chief Product Officer at Cielo, called this shift "a quantum leap forward." Not just a productivity boost, but a fundamental reframing of how talent acquisition operates.
The AI doesn't just do tasks — it evaluates what's working, adjusts its own approach, and integrates human feedback. That's the power of agentic systems — continuous improvement at scale.
Chipotle's use of Ava Cado — a virtual team member built on agentic principles — led to a reduction in average hiring time from 12 days to just four. The AI assistant handles:
For a high-volume hiring environment like fast-casual restaurants, that's not just a nice-to-have — it's a game-changer. What stands out here is not the novelty of an AI chatbot, but the level of responsibility handed over to it. This is no longer just a support tool. It's a functional member of the team, running point on a critical business function.
Not all AI is created equal. Many current business tools use AI for narrow tasks — to summarize text, generate images, or automate email responses. But agentic AI operates at a different level.
Here's how it stands apart:
Agentic AI handles multi-step processes with minimal intervention. It doesn't just automate a task — it orchestrates a sequence of tasks, makes decisions based on context, and adapts as it learns.
These systems integrate multiple data sources, understand goals, and make informed choices — often better and faster than humans working across siloed systems.
Unlike traditional automation, agentic AI learns from outcomes and adjusts its behavior. This means long-term efficiency gains and fewer manual adjustments as the system matures.
Scaling agentic systems doesn't require one-to-one human oversight. Once implemented, these agents can execute parallel tasks, multiplying the output of a single team.
There's a noticeable shift in the market: from curiosity to capability. The organizations seeing real returns from AI aren't the ones running pilots. They're the ones treating AI as a core competency.
So what's stopping others from doing the same? In most cases, it's not lack of opportunity — it's lack of clarity around how to start, where to apply AI meaningfully, and how to measure ROI beyond vague efficiency metrics.
This is exactly where partnering with external experts matters. Implementing agentic AI solutions doesn't start with picking a model — it starts with identifying business processes where intelligent autonomy can deliver material value. From there, the focus should be on:
The companies getting it right aren't just building software — they're designing new operating models.
The opportunity is real, and so is the challenge. Agentic AI requires more than just technical implementation — it requires cultural and structural alignment.
Here's how we advise executive teams to get started:
Understand where your organization stands in terms of data maturity, process clarity, and cultural readiness for AI integration.
Focus on workflows that are repetitive, rules-based, and time-consuming, but still involve decision-making.
Whether it's for AI leadership, project delivery, or staffing, working with the right partner helps navigate complexity and get to value faster.
Prove value in a single business unit, then expand into adjacent workflows. Agentic AI scales best with a phased, outcome-driven roadmap.
AI is no longer a strategic question — it's an operational one. If you're still wondering how to "bring AI into the business," it's time to shift the conversation to how your business will operate when AI is deeply embedded across teams and functions.