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Liam McCaffrey

Head of Performance Marketing

Marketer with a background in SRM and science communication.

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By 2028, one in three businesses will use agentic AI 

By Liam McCaffrey on February 10, 2025

Things are getting serious for artificial intelligence (AI).

The UK and US governments both recently announced extensive plans for and investments in AI. At the same time, more businesses are sharing success stories of the results they’ve delivered through applying AI to areas like inventory management.

Now, there’s a new AI that’s expected to transform the way we make decisions — one that Gartner predicts will be integrated into 33% of business solutions by 2028. It’s called agentic AI.

In this article, we’re going to explore what agentic AI is and how it can be implemented to optimize inventory management and pricing decisions.

What is agentic AI?

Unlike traditional automation, which follows strict rules and predefined workflows, agentic AI can set its own course based on a broader objective. Once given a goal, it can decide how to achieve it and adapt to new information. When enabled to do so, it can even act itself without needing step-by-step human input.

It can analyze situations, determine the best course of action and even delegate tasks to other systems. Rather than simply executing predefined tasks, agentic AI can handle complex decision making, work across multiple systems and continuously refine its approach.

Agentic AI is gaining momentum because it represents a fundamental shift in how businesses use AI. Until now, AI has been assistive, meaning it has primarily provided insights, suggested actions or automated repetitive tasks within predefined limits.

Two of the most immediate and high-impact applications for agentic AI are inventory management and pricing optimization. These areas require constant, data-driven decision making — and agentic AI is already proving its ability to make these processes faster and more efficient.

How can agentic AI help my business?

Agentic AI in inventory management

Modern supply chains are too complex for static decision-making models. Fluctuations in demand, stockouts and logistics constraints require constant adjustments. 

Yet, many businesses still rely on reactive decision making, with hours spent manually adjusting inventory levels based on limited calculations and clunky spreadsheets full of information. This leads to excess stock, shortages and inefficiencies that cut into profitability.

Gartner’s research highlights the role agentic AI will play in improving inventory decisions:

Agentic systems will change the future of decision making. They can quickly analyze complex datasets, identify patterns and act. This will avoid labor-intensive data modeling, lead to better problem solving, reduce time to action and enable new concepts of scale.

Gartner

Instead of managers spending hours reviewing data and making incremental adjustments, agentic AI continuously analyzes historical sales data, surfacing recommendations that businesses can act on immediately.

Agentic AI in pricing

Pricing decisions must constantly adjust to shifting demand and price elasticities. Yet, most businesses still rely on outdated pricing models, setting prices based on historical data rather than real-time market conditions.

Gartner predicts that by 2028, at least 15% of day-to-day work decisions will be made autonomously through agentic AI. This will include pricing adjustments based on AI-driven insights, ensuring businesses maximize revenue without eroding margins.

Rather than waiting for analysts to adjust prices manually, agentic AI can:

  • Identify opportunities for margin optimization based on sales and demand data
  • Adjust promotional pricing dynamically, ensuring discounts are targeted and profitable
  • Prevent unnecessary markdowns, helping businesses avoid revenue losses

Co:Driver™, Peak’s agentic AI assistant for inventory and pricing

Co:Driver™ is Peak AI’s agentic AI assistant — a tool designed to help businesses make smarter, faster decisions by surfacing real-time insights in a way that’s easy to act on. Instead of waiting on static reports or digging through dashboards, teams can ask Co:Driver™ direct questions and get AI-powered recommendations instantly.

Think of Co:Driver™ as your own ChatGPT, but built on your business data and processes.

You can ask it questions like:

  • “What SKUs are at risk of running out in the next 30 days?”
  • “Which products have excess stock that should be moved first?”
  • “What’s the optimal price point for Product X?”
  • “How would a 5% price increase affect sales volume and revenue?”

It works across inventory management and pricing, two areas where slow decision making can cost businesses millions. For inventory, Co:Driver™ works alongside Peak’s Inventory AI product, analyzing demand patterns, supplier timelines and stock levels to highlight risks and suggest actions before problems arise. At the same time, it connects with Pricing AI, helping businesses optimize pricing based on real-time market shifts, competitor movements and stock availability.

Co:Driver™ connects these decisions together. Instead of treating inventory and pricing as separate problems, it links them, so teams can see how one affects the other. Co:Driver™ helps businesses get the right stock in the right place, at the right time and at the perfect price point that maximizes sell through and margin.

Getting ahead in the age of agentic AI

By 2028, agentic AI will be a standard part of business operations. Companies that integrate it now will be in a stronger position to manage their inventory, pricing, and overall decision making more effectively.

Co:Driver™ is already making this possible. It gives businesses direct access to AI-driven recommendations, helping them optimize inventory and pricing, with easier access than ever to AI where they can ask questions about their data and get instant answers. .

If you want to find out how agentic AI can help your business, reach out to one of our team at Peak. Also be sure to join our upcoming webinar, What is agentic AI, anyway? on Thursday 27 February.

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