Category Management: Key Insights for 2026 From ChAI

Our recent series on the discipline of category management (CatMan) explored how businesses implement category management, its role in procurement and the benefits it can deliver.

Read our definition of CatMan as a central procurement discipline, which includes a list of the potential benefits its deployment can afford.

To round up the perspectives it covered, we have invited some of the category management and related solution providers to answer a few targeted questions about category management and how their solution supports it.

Today we hear from Tristan Fletcher, CEO of market intelligence solution ChAI.

How is CatMan evolving and where does technology fit in that evolution?

“Category management is undergoing a structural shift: from a cost-focused discipline to a risk-intelligent one. Procurement leaders now need to understand price volatility, supply disruption risk, sustainability regulations and geopolitical uncertainty, because:

• Planning cycles are shortening. Commodity markets move faster than annual sourcing cycles, driving a need for continuous, near-real-time intelligence.
• Supply chains are more complex. Scarcity, tariffs and regulatory shifts require deeper knowledge across regions and suppliers.
• Cross-functional collaboration is increasing. Category managers increasingly sit at the intersection of procurement, finance, ESG, risk and operations.

“Technology is therefore critical to: automate the lower-value work (searching, monitoring, gathering data, etc.); provide predictive insights and scenario analysis; make market information more accessible to non-experts and accelerate decision-making through shared intelligence and collaborative tools.”

What are the main pain points you see among customers trying to implement CatMan activities?

“Common pain points include:

• Lack of reliable, real-time market intelligence
• Market uncertainty driven by global geopolitical shifts
• Internal misalignment and competing priorities.
• Budget constraints limiting access to advanced tools
• Embedding risk management into day-to-day decision-making
• Securing long-term physical supply in volatile markets

“A subtle but important issue is that many teams remain overly dependent on supplier-provided intelligence, creating information asymmetry during negotiations.”

And the challenges of digitizing them?

“Data quality and readiness – procurement data is messy, sometimes inconsistent and often can be siloed. Spend classification, inconsistent material coding and the likes make automation more difficult.

“Integration with existing workflows and processes – most organizations with a small to medium-sized procurement team have processes and procedures in place for how their procurement or category management team gathers data and makes decisions. These processes are as diverse as the companies they serve, so integrating new solutions into the pre-existing practices is a challenge. This also applies to integration with legacy tools.

“Building trust with AI tools – this is one of the areas of business where relationship management is a key requirement, and trust is built on relationships. In such a context, establishing trust with a ‘black box’ style AI solution is not easy, and takes time.

“Skill gaps – digitization of some of these challenges requires new skills that were historically not as relevant in category management roles (like data analytics and LLMs), digitization would require additional skills and training.

“Difficulty capturing tacit knowledge – much of the expertise associated with individual categories lives in people’s heads, be that through knowledge of past behavior, relationships that have been developed and are maintained by individuals or through expertise in individual categories. In some markets, even to this day, the most trusted source of information can be ‘the X Guy’ – ultimately a single individual with deep expertise in a category. Capturing such expertise through digital systems is a challenge.

“Rigid processes, low risk appetite and general slow speed to react make it much harder for some organizations to digitize and leverage some of the new solutions available.”

What role does AI play in supporting category managers today?

“AI is increasingly central in:

• Price forecasting and volatility prediction
• Supply chain risk monitoring, including geopolitical, regulatory, supplier, financial and logistics risks
• Automated information gathering, summarization and market monitoring using LLMs
• Decision support, where AI contextualizes market shifts into procurement-ready insights
• Creating faster, more informed negotiation prep, from market summaries to supplier-specific insights

“The technology is ready – the challenge is helping people see the impact on their everyday workflow.”

What differentiates organizations that successfully adopt CatMan technology?

“An innovative mindset from the top down – leaders that push for innovation successfully in their organizations and enable and facilitate the adoption of new solutions make a big difference.

“Flexible and agile culture to move quickly and fail fast in a complex and volatile environment.

“Having a senior internal champion for adoption of new technologies who is committed to innovation.

“Expectation management – technology isn’t a panacea, and it’s important to benchmark your expectations correctly.”

How well are CatMan tools being adopted and how do people perceive value?

“People see value when tools produce measurable improvements in their daily work, like:

• Faster access to reliable market intelligence
• Better negotiation outcomes
• Clearer understanding of price drivers
• Time savings compared with manual research
• Greater confidence in planning and budgeting

“Adoption is steadily rising, but maturity varies. Tools that integrate easily, demonstrate value quickly and reduce complexity tend to succeed fastest. Tools that require process overhaul face a slower adoption curve.”

How does CatMan interact with other procurement-related areas?

“Category management increasingly sits at the center of:

• Procurement and commodity price risk, requiring closer collaboration with enterprise risk teams
• ESG and sustainability compliance, from CBAM reporting to circular economy regulations to carbon-adjusted cost modeling
• Supplier collaboration, especially on forecasting, capacity planning and risk-sharing mechanisms such as index-based pricing or volume guarantees

“As complexity increases, CatMan becomes a cross-functional strategic intelligence hub linking finance, operations, risk and suppliers.”

In terms of your solution:

Given the proliferation of AI-driven content sources, how do you ensure that intelligence remains validated, timely and actionable for sourcing decisions rather than simply descriptive?

“ChAI’s focus has always been on predictive accuracy and decision usefulness, not simply presenting data. We ensure this in several ways.

Rigorous model validation: All our forecasting models are continuously benchmarked against futures markets, physical prices and out-of-sample tests so clients can trust that our signals are genuinely predictive rather than descriptive.

Multi-source data triangulation: We blend market, macroeconomic, flows, freight, FX and sentiment datasets. This helps us avoid the pitfalls of single-source AI systems and ensures robustness even in volatile markets.

Explainability built in: For every forecast we show the underlying drivers, whether price movement is driven by exchange rates, inventories, freight or flows. This transparency helps procurement teams defend and operationalize decisions.

Real-time updates: Markets move quickly, so our models are recalibrated frequently to incorporate the latest price, macro and supply-demand signals, ensuring clients have timely and actionable insights during budgeting, negotiations and hedging windows.

Client feedback loop: We maintain close partnerships with procurement teams to ground our development in what ‘actionable’ really means for them – ultimately shaping our roadmap around their real workflow pain points.”

How do clients typically operationalize your aggregated supplier and market insights within their sourcing or category strategy workflows?

“Most clients integrate our insights at key decision points in the sourcing cycle. Typical examples include:

• Budgeting and annual planning: Using our forecasts to stress-test budgets and scenario-plan volatility.
• Supplier negotiations: Benchmarking supplier quotes against our predictive curves and understanding the drivers behind recent price moves.
• Risk planning: Monitoring short-term market risks such as currency shifts, freight spikes or inventory shocks.
• Hedging and contracting windows: Aligning procurement and treasury by using ChAI to time hedge execution more effectively.

“Operationalization takes two forms:

• Our web app, which gives immediate access to market intelligence and the underlying drivers without requiring process change.
• Deep API or data integrations, where our forecasts feed directly into a client’s existing spreadsheets, dashboards, ERP systems or sourcing suites.

“Large teams cannot simply rewire their decision processes overnight – so our philosophy is to fit seamlessly into their existing workflow, not force a new one.”

How do you embed predictive or prescriptive analytics into your solution?

“Our roadmap focuses on moving from ‘what is likely to happen’ to ‘what you should do about it.’ We are currently embedding:

• Carbon-premium pricing that automatically adjusts raw material cost models using CBAM and ETS projections
• Hedging suggestions, highlighting moments where taking action could reduce cost exposure
• Early-warning indicators for volatility, supply tightness and macroeconomic triggers
• Scenario planning tools, enabling teams to model risk across multiple price, carbon and FX pathways

“The objective is a system that proactively highlights shifts and guides users toward the most risk-aware sourcing choices.”

How do you ensure your platform evolves with regulatory, sustainability and supply-chain complexity trends? 

“We stay aligned with the evolving landscape through continuous engagement with clients and industry advisors, monitoring major regulatory developments, building modular architecture that lets us adapt quickly as new requirements emerge and fast iteration cycles to incorporate new datasets, new regulatory logics and updated carbon pricing models.

“Our aim is to ensure clients are never caught off-guard by emerging regulatory or market risks.”

If you could change one thing about how the market perceives or approaches CatMan, what might that be?

“We would encourage organizations to be more open to innovation and less risk-averse in trying new solutions.

“Many of the tools needed to navigate today’s volatility already exist – they simply require internal champions willing to drive adoption. CatMan is evolving into a strategic, data-driven discipline, and organizations that embrace this shift early will be far better prepared for the increasing complexity of global supply chains.”

Many thanks to ChAI for being part of this series.

You may find this handy, free-to-download Guide to Spend Analytics useful.