The rise of agentic AI and the future of convenience retail
Artificial Intelligence has moved well beyond being just that technology that answers questions or generates nice-looking text.
It is evolving into something far more powerful: agents that make decisions, execute tasks, and operate autonomously without needing a human to push a button at every step.
And convenience retail was one of the first industries to truly feel this shift.
At the Conexxus Annual Conference 2026, held in January, executives, engineers, and technology specialists gathered to discuss a question that sounds like science fiction but is already happening behind the scenes of daily operations:
What if stores could think for themselves?
We are not talking about a system that alerts you when inventory is running low. We are talking about autonomous agents that detect an incoming weather change, anticipate a spike in demand for a specific product, automatically adjust the order, and even notify the supplier — all without any human intervention.
Sounds like a lot? Maybe. But that is exactly the direction technology is heading, and the companies that understand this now will be ahead of the curve.
In this article, we are going to break down what happened at the conference, what this so-called agentic AI actually is, how it is transforming everything from inventory management to mobile commerce, and why the balance between automation and human presence is still the most critical piece of this equation. 🚀
What is agentic AI and why it changes everything
For years, Artificial Intelligence worked as a reactive tool. You asked, it answered. You fed it data, it generated a report. The logic was always the same: a human in control, the AI executing. But the concept of an autonomous agent breaks that dynamic entirely. Instead of waiting for a command, the agent observes the environment, interprets what is happening, and acts on its own based on previously defined goals. This is a paradigm shift that goes well beyond a software update.
Bradford Loewy, Director of Product Solutions at Bulloch Technologies, explained during a panel at the conference that AI agents use artificial intelligence techniques to make decisions, execute actions, and achieve goals autonomously, within parameters set by humans. The fundamental difference from traditional generative AI is precisely this ability to act without needing step-by-step approval.
Clerley Silveira, Engineering Manager at Invenco by GVR, offered an example that makes it all click. Today, generative AI can help you plan a vacation, suggesting a day-by-day itinerary with flights, activities, accommodations, and restaurants. Agentic AI takes it further: based on your preferences and rules you have defined, it books everything for you without you lifting a finger.
When we get to the stage where you no longer need to take the action yourself, that is when we will have true agentic AI. And that is what is going to be really transformative, Silveira said during the event.
In practice, an autonomous agent can chain multiple actions in sequence, make micro-decisions along the way, and self-correct when something goes off plan. Imagine a store manager who never sleeps, never forgets to check inventory, and can even predict what will happen in the next few hours based on weather data, sales history, and customer foot traffic. That is essentially the promise of agentic AI applied to retail.
What stood out at the Conexxus Annual Conference 2026 was the maturity with which this topic was presented. It was not a discussion about the distant future. It was a conversation about real implementations, ongoing pilots, and lessons learned from those who are already putting these systems to work. The experts were clear: intelligent automation already exists, already works, and is already delivering results. The question now is how to scale it responsibly.
The agentic store of the future
Many convenience store operators already use some form of AI for automation. A common example is the inventory forecasting report that helps optimize what to order and when. But there is a catch: a human still needs to actually place the order. Or maybe the software can already place orders automatically based on replenishment triggers, but without factoring in dynamic variables like weather, local events, promotions, or supply chain disruptions.
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Michael Munz, Marketing Operations Manager at Petrosoft, made it clear during the conference: where agentic AI really starts to come into play is when it makes these tasks trivial. These processes that we rely on, the agent can start taking over for us.
And the most interesting part is that this concept applies to virtually every area of convenience store operations, from the fuel court to the food counter.
Fuel and tank management
On the forecourt and in underground fuel storage, Jack Dickinson, Director of Partner Development at Dover Fueling Solutions, explained that operators are already working on reactive and preventive agents capable of responding to existing automated systems.
Today it is already possible to monitor gauges, check what is in the tanks, track deliveries, and measure fuel flowing out. But Dickinson sees a future with automated technician dispatching. Imagine an agent that knows the location and schedule of every maintenance technician and can reroute them as new priorities emerge. Even better: imagine an agent that knows exactly which parts are in each technician’s truck and can direct the right person to the right location based on the parts most likely to be needed there.
Preventive and operational efficiencies can really be automated. We can allow systems to start making decisions and connect to other aspects of operations that are currently siloed, Dickinson highlighted.
Smart inventory management, no guesswork
One of the most discussed topics at the conference was the impact of Artificial Intelligence on inventory management. And it is easy to see why. Poorly managed inventory is either money sitting idle or, worse, a customer staring at an empty shelf. Losses from stockouts and excess inventory add up to billions per year across global retail, and a large portion of those losses happen simply because traditional systems cannot react fast enough to changes in demand.
Munz, from Petrosoft, described the current landscape precisely: Inventory today is a living system. It is connected to supply chain realities, seasonal patterns, customer demands, loyalty programs, manufacturer incentives, and increasingly to things like shrinkflation and tariffs.
With Artificial Intelligence agents, this scenario starts to change in a tangible way. The system can monitor the turnover rate of each product in real time, cross-reference that data with external variables like weather, holidays, local events, and even consumer behavior trends, and then automatically adjust purchase orders. Instead of restocking simply because a minimum threshold was reached, agentic AI will be able to consider everything around it. It can delay or accelerate an order because it detected an incoming promotion, a weather event, or a shift in customer demand driven by price sensitivity.
All of this happens continuously, without a manager needing to review spreadsheet after spreadsheet. The result is a much leaner operation with less waste and more accurate replenishments. 📦
Foodservice: thousands of decisions that can be taken off your plate
The food segment within convenience retail is one of the most complex operations in the industry, according to Mike Weber, Chief Growth Officer at Upshop. And the current reality does not help: many operators still manage foodservice with spreadsheets, mental math, and the previous day’s sales data. With margins tightening and labor pressure increasing, this approach is becoming unsustainable.
That method puts the burden on your team to make a lot of daily decisions in very little time and under a lot of pressure, Weber said. The computer should be focusing on these things that can be automated so the team can focus on what is most meaningful.
Weber explained that in foodservice, AI should track every ingredient from the moment it comes through the door, help operators decide how much food to produce by location and time of day, monitor waste, guide teams on how to handle markdowns, and forecast inventory needs for the next days to weeks ahead.
According to him, store-level demand forecasting is the most realistic and impactful starting point for AI in foodservice. With that approach, it is possible to achieve 98% to 99% accuracy, which translates into extremely efficient stores.
When agentic AI is activated and connected to forecasting systems, it will be possible to generate even better recommendations and optimize foodservice operations end to end. The agent can be trained to focus on the most important metrics for each store, anticipating what needs to change based on the signals it identifies, whether they are recurring patterns from a supplier, variations in forecasts, or market behavior shifts.
Mobile commerce and the new consumer journey
If you asked Gray Taylor, former Executive Director of Conexxus, what will define the future of convenience, the answer would be one thing: mobility commerce, and agentic AI is the driving force behind it.
The concept is fascinating. Your car will function as a connected piece of the convenience ecosystem. You will be able to tell it to stop at your favorite station to fuel up, place a food order on the way, or buy a product while the system automatically verifies your identity and age. Your vehicle will know your loyalty program and be able to pay for all of those products before you even arrive. License plate recognition technology will check your car in at the pump.
But Taylor issued an important warning: there is a lot of work needed to make all of this a reality.
We have, and I cannot emphasize this enough, a freight train coming at us called agentic shopping. It is being driven by consumers’ ability to find you online, by systems knowing your real-time inventory and what you have in your store and your price book, Taylor said. AI is going to make pragmatic decisions for the consumer, like choosing between making two right turns to go to one store or two left turns to go to a favorite. AI is going to start deciding that and learning preferences. So we have a lot of work ahead of us and it is going to be a huge operational challenge.
Beyond the convenience for the end consumer, this integration of mobile commerce and intelligent automation also generates valuable data for operations. Every user interaction with the app feeds the Artificial Intelligence system, which learns continuously and refines its predictions and recommendations. It is a virtuous cycle where the experience improves for the customer and the operation becomes more efficient for the business at the same time. 📱
Automation with responsibility: the human role that cannot be forgotten
With all of this, it would be easy to conclude that the future of retail is fully automated, with no humans in the loop. But the Conexxus Annual Conference 2026 was very emphatic on one point: automation and human presence are not opposites — they are complementary.
The conference speakers made one thing very clear: we should not automate just for the sake of automating. Munz, from Petrosoft, summed it up well: There is a point where automation becomes counterproductive, especially when it overrides store-level judgment. That is a human thing, and we need to value it.
The retailers who succeed will be the ones who understand what to automate, what to protect, and where humans need to remain central to maintaining consumer trust.
The retailers who win will be those who deploy technology with clarity, balancing automation with human oversight to build trust, preparing for risks and evolving guidelines, and recognizing that inventory is just one piece of a much larger AI-powered e-commerce platform, Munz added.
The model that has worked best in the implementations presented at the conference is the so-called human-in-the-loop approach, where the autonomous agent handles most of the operations but a human remains the point of supervision and decision-making in scenarios of greater complexity or risk. It is not about removing humans from the equation — it is about freeing people from mechanical tasks so they can focus on what truly matters: customer relationships, innovation, and business strategy. ⚙️
Security and governance: the next generation of protection
Without robust security and proper governance, AI is not innovation — it is exposure. That warning came from J.B. Branch, a big tech accountability advocate focused on consumer rights and data privacy at Public Citizen.
For an industry that touches millions of consumers every day, using AI as part of the core business infrastructure completely changes the risk profile. When failures happen, you lose consumer trust, Branch warned. We want to scale AI innovation. That is a good thing. But we do not want to erode consumer trust.
Branch raised a point that deserves special attention: as we advance toward agentic AI, we will have one company with thousands of AI agents interacting in cyberspace with thousands of agents from another company, without much human oversight. And that is concerning when errors or harm occur.
One of Branch’s strongest warnings was about vendors and data sharing. He recommended that retailers understand where their data is stored, which vendors have access to it, and whether that data is being reused to retrain AI models.
Before deploying AI, Branch recommended that retailers consider:
- Defining data boundaries — what the AI can and cannot access
- Locking down vendor contracts — data usage, retention, and server locations
- Planning for failures at scale, not just for isolated cases
- Maintaining human accountability at every stage
You need clear internal rules about what data you are using, how long you retain it, and what it is used for, Branch reinforced. 🔒
Putting yourself out of business (the right way)
Frank Gleeson, CEO and President of NACS, started his career on the front lines of his family’s business and carries a motto: If you are not serving the customer, you are serving someone who is.
During his keynote at Conexxus on innovation and technology in convenience, he emphasized that store employees have the hardest job in the organization, and that any innovation or technology that does not make their lives easier will fail.
Technology is a great enabler, Gleeson said. When you think about technology, it needs to be about simplifying things and removing friction.
The best technology tools, according to him, simplify tasks instead of adding new steps, reduce the cognitive load on employees, and eliminate unnecessary manual work and redundancies.
Gleeson recalled his experience as President and CEO of Aramark Northern Europe, when he worked with a computer vision self-checkout company in its early days and deployed the technology in sports stadiums. It was quite transformative at the time, and the goal was always to find something that would make the purchasing process easier and faster for customers, especially at high-volume venues or where labor costs were particularly high.
He made a point of clarifying: this is not about cutting headcount. Better technology leads to better service, not fewer people. When the tools do their job well, employees can focus on what only humans do best.
And with successful innovation also comes failure. Not every idea will work, and they do not always work quickly. Referencing the self-checkout example, Gleeson shared that the rollout took years, not months, to scale. And many other technologies tested in stadiums simply did not pan out.
His advice for retailers: test small, fail fast, and scale only what drives repeat behavior.
In a Q&A session with panelists including Chris Bambury (President of Bambury Inc.), Lonnie McQuirter (Director of Operations at 36 Lyn Refuel Station), Varish Goyal (CEO of Vintners Distributors, Au Energy, and Loop Neighborhood Markets), and Jigar Patel (Vice President of SAASOA USA and CEO of Fastime), the group pointed to examples of where technology delivers real value for operators:
- Mobile ordering and pickup that actually save time
- Integrated car wash and fueling experiences
- Contactless entry points and payment flows
- Technology that enables fast order customization
- AI-assisted checkout that speeds up transactions
- Automated cleaning and maintenance that free up employees for customer service
Innovation is not always about novelty or being the first to market. It is about introducing the right technologies that solve the right problem to transform a business.
Twenty-five years ago, the late Steve Sheetz, former President, CEO, and Chairman of Sheetz, said his vision was to create a version of Sheetz that would put the Sheetz he was leading out of business. Gleeson closed his remarks by challenging the audience: how would you put your own business out of business today, if you were to innovate and grow? 💡
What to expect from the next steps
What became clear at the conference is that we are at the beginning of a transformation that will deepen over the coming years. Companies that have already started experimenting with autonomous agents, even on a small scale, are accumulating knowledge that will be decisive as the technology matures further. The cost of entry is dropping, the tools are becoming more accessible, and the use cases are multiplying at an impressive pace.
For convenience retail specifically, the combination of predictive inventory management, personalized mobile commerce, and automation of operational processes represents a massive opportunity to gain efficiency and improve the consumer experience at the same time. And all of this is being orchestrated by Artificial Intelligence systems that learn, adapt, and continuously evolve based on the data generated by the operation itself.
But the most important message from Conexxus 2026 might be this: the power of agentic AI in inventory, foodservice, fuel, and mobile commerce is something that looks easy to implement, but it is not. It is about trust. Consumer trust, trust in the data, trust in the systems, and trust in the people who oversee all of it.
The question companies need to answer now is no longer whether they will adopt this technology, but how they will do it strategically, responsibly, and aligned with their business goals. The pieces on the board are already in motion, and those who understand this dynamic clearly have a real advantage ahead. 🎯
