If you have been following conversations around the future of work and AI, you have probably started hearing about a role that is gaining serious attention inside companies: the AI workflows role.
Business Insider recently covered it with Jiaona Zhang, Chief Product Officer at Laurel, calling it “the new Biz Ops” and one of the most important emerging positions for businesses that want to stay competitive.
The idea behind this AI Ops role is straightforward: it focuses on identifying areas inside an organization that can be optimized using AI, designing the workflows to make that happen, and keeping those systems running and improving over time. According to McKinsey’s 2025 State of AI report, 78% of organizations are already using AI in at least one business function, up from 55% just two years ago. The pressure to implement AI properly is real, and it is growing fast. For many business owners, this raises an immediate and practical question: do we need to hire for this internally?
The answer depends on where your business is right now. But for a significant number of small and mid-size companies, the smarter path is not building this internally from scratch. It is finding the right partner who can deliver the same results with less risk and less overhead.
Why the AI Workflows Role Is Becoming a Core Business Function?
AI is no longer just a productivity tool that individual team members use independently on their laptops. It is becoming operational infrastructure, something that affects how an entire business runs at the process level.
Companies that are seeing real, measurable results from AI are not just handing their team access to ChatGPT and calling it done. They are mapping their operations, identifying which tasks and processes are strong candidates for automation or AI-assisted work, building custom workflows around those opportunities, and then training their teams to work inside those new systems consistently.
That requires someone to own the process end to end. Without clear ownership, AI adoption inside a company tends to stall. Teams adopt tools inconsistently, workflows go undocumented, results are hard to measure, and the initial excitement fades without producing anything that actually moves the business forward.
The AI workflows role exists to prevent exactly that. It is the function that turns AI from a scattered experiment into a structured, repeatable business advantage. At Eligeo.ai are noticing that scaling is the real bottleneck: many companies are running pilots, but very few are seeing transformation at the operational level.
What This Role Actually Requires on an Ongoing Basis
To understand why this is a meaningful investment, it helps to look at what the AI workflows function actually involves day to day.
- It starts with an operational audit, meaning someone has to understand your business well enough to identify where AI creates real leverage. That is not something that happens in a week. It requires time, access, and genuine familiarity with how your team works and where the friction lives.
- From there the work moves into tool selection and workflow design. There are hundreds of AI tools available right now, and the right ones for your business depend entirely on your existing processes, your tech stack, and your specific goals. Choosing the wrong tools wastes time and budget. Implementing the right tools poorly produces the same result.
- Once workflows are built, someone needs to manage the rollout, help the team adapt, handle the friction that always comes with operational change, and then keep iterating as both the technology and your business needs evolve.
This is an ongoing function, not a one-time project. That distinction matters a lot when you are thinking about how to approach it, and it connects directly to something we posted about earlier: building the right foundation before jumping into AI implementation. Without that foundation, even the best AI workflows will underdeliver.
If You Are Thinking About Hiring for This Role
Hiring someone specifically for AI workflows is a legitimate and valid option if your business is at the right stage. If you have the budget, the time to recruit carefully, and the internal clarity to onboard and manage that person well from day one, a strong AI Ops hire can be a serious long-term asset.
The challenge most businesses run into is that they are not quite sure what they need yet. They know AI should be doing more inside their operations, but they have not mapped out what that looks like specifically for their business, their team, and their current tech environment.
Hiring before that clarity exists tends to create a frustrating experience on both sides. The role ends up loosely defined, hard to measure, and slow to produce results because the person you bring in spends too much time figuring out what to build instead of building it.
Research on small business AI adoption consistently points to capability confidence and training gaps as the top barriers. It is not that business owners do not want AI integrated into their operations. It is that most do not yet have the internal infrastructure to absorb and manage that function well, which is exactly what makes the next model worth considering.
How Companies Are Getting the Same Output Without Building It Internally
This is where the fractional AI team model makes sense, and it is the approach that works best for a growing number of growing businesses.
Instead of hiring and building this capability from scratch while simultaneously trying to run your business, you partner with an external team that already has the expertise, the tools, the methodology, and the implementation experience to move faster and with significantly less risk.
At Eligeo.ai this is the model we built our practice around.
We function as your fractional AI workflows partner, which means we come into your business, learn how your operations actually work, identify the highest-leverage AI and integration opportunities for your specific situation, design and implement the workflows, and then stay with you as the systems evolve. You get the results of an experienced AI Ops function without the overhead or uncertainty of building one internally.
You have probably already tried some AI tools, seen some potential, and realized that taking this to the next level requires a more structured approach than what your current team can manage on top of their existing workload. That is the gap we fill, and we fill it as a long-term partner, not as a consultant who hands you a report and leaves.
What Working With Eligeo.ai Actually Looks Like
Every engagement we run follows our C.O.R.E. methodology, a four-step process we developed to make sure AI and operational changes actually stick inside a business, not just look good on paper.
- It starts with Consultancy and Blueprints. Before we touch a single tool, we map your operation completely. We pinpoint exactly where your team is losing time, where manual work and duplicate data entry are quietly costing you money, and what your business actually needs before any software gets installed. This is where most implementations go wrong: tools get selected before anyone understands the problem. We flip that order intentionally.
- The second step is Operational Architecture. Once we understand your operation, we design the load-bearing structure of it. This includes mapping the workflows your company needs to scale without creating new chaos, setting a clean data foundation so your reporting is reliable, and making sure your different systems are connected so information flows the way your business actually moves.
- From there we move into Rapid Build-Out, where we build your environment. We configure everything to match the exact way your team works, not a generic template, and then we push the system hard through stress testing to make sure it holds up under your real workload before anyone depends on it.
- The fourth step is Employee Onboarding, and this is where most implementations quietly fail. Building something great means nothing if your team does not use it confidently. We train the main user so they know exactly what to do from day one, and then we track real adoption after go-live to make sure the system is actually being used. Our extended enablement keeps us involved long after launch so your team keeps improving and gaining confidence over time.
The Bigger Picture
The companies that will have a real competitive advantage over the next several years are not necessarily the ones with the biggest AI budgets. According to multiple industry surveys, 92% of companies plan to increase their AI investment over the next three years, but only 1% of leaders currently describe their organization as mature in AI deployment. The gap between intention and execution is enormous, and the AI workflows function is what closes it.
If you are a business owner or operations leader who knows AI should be doing more inside your company but has not found the right path to make that happen in a way that actually sticks, this is worth a real conversation.
The question is not whether your business needs this function. It is how you staff it in a way that makes sense for where you are right now.
Ready to explore what a fractional AI workflows partnership would look like for your business?
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