Pigment Uncertainty Index: Q1 2026

Pigment is an organization that specializes in mitigating uncertainty - a task that, for many business leaders, is becoming ever more difficult.

As that trend shows no sign of abating, we wanted a way of tracking how the market reacts to disruptive forces like turbulent geopolitics, supply chain breakdowns, and the AI revolution.

The Pigment Uncertainty Index is a new initiative that surveys finance leaders from the US, UK, France, and Germany. We track indicators of uncertainty and sources of disruption on a quarterly basis and provide detailed analysis across a variety of different dimensions.

This is the first edition of the index. While I think the insights we’ve uncovered already are incredibly valuable to business leaders, what we’re especially excited about is seeing how these trends evolve over time.

Let’s get into the data.

Part 1: Past performance and future outlook

AI maturity is the best predictor of growth in the past year

We calculate expected revenue growth by asking our respondents to predict a revenue for a range of five scenarios for the year ahead (lowest, low, middle, high, and highest). We then ask them to assign a probability value to each scenario. From that information, we’re able to calculate what their ‘average’ prediction is for the year ahead.

Businesses saw a 9.3% increase in revenue in the last year.

The US saw the strongest growth of any region at 10.5%, followed by the UK at 8.2%, Germany at 7.7%, and France at 5.8%.

Technology (11.4%), finance and insurance (10.5%), and construction (9.8%) were the best-performing industries, with healthcare (5.6%), wholesale trade (6.3%), and manufacturing (6.8%) recording the lowest growth.

But splitting revenue growth by AI maturity reveals the best predictor of performance: companies who identified their internal capabilities as ‘mature’ (the highest in the survey), grew 18.1% over the past year - almost 12% faster than those at the lowest maturity stage, who grew revenue by 6.2%.

Rosy forecasts

Looking ahead, the picture is one of optimism, with the overall expected revenue growth for our sample at 11.2% - stronger than last year’s actual performance of 9.3%. 

The most optimistic forecasts come from different industries than the highest performing in the past year (tech, FSI). Construction is expecting a bumper year ahead, leading the pack with a 14% expected increase. Wholesale trade follows with 12.9% - interesting given the sector’s relatively weak performance in the past year.

The AI maturity data tells the same story as before: expected revenue scales with AI maturity, with leading companies predicting over 5% more growth in the next year.

Geographic differences are less pronounced than those for performance in the past year: the UK has the highest expected growth at 12.8%, then the US at 11.3%, France following at 10.4%, and Germany lowest at 10.1% - all higher than the average growth figure for the past year.

Manufacturing (9.5%) and healthcare (7.5%) have the gloomiest outlooks, but again think the year ahead will be better than the one that’s just passed.

Part 2: Anxiety abounds

Uncertainty creeps into the boardroom

Despite strong growth and even stronger revenue predictions, it doesn’t seem as though success is buying anyone confidence. 

Perceived uncertainty is rising: 41.5% say it’s higher than 6 months ago, with 34.5% saying unchanged, and just 24% lower.

Despite being the best revenue performer, US finance leaders are by far the most anxious about the future. 48% say uncertainty is higher than six months ago, and crucially, 15.2% say it is "much higher" - compared to just 4.2%, 4.5%, and 5% for the UK, France, and Germany respectively.

The UK, by contrast, is the most stable-feeling market, with 41% saying uncertainty is "about the same".

Industry-wise, the strongest performers - technology and finance/insurance - are the most likely to say uncertainty has risen compared to six months ago. Over 45% in both cases reported higher uncertainty. 

Another interesting observation is that perceived uncertainty gets higher with seniority. VPs and CFOs are dramatically more likely to say uncertainty has increased - 51% say it is somewhat or much higher, directors 43%, and just 36% of managers/senior managers. 

This is surprising given more senior respondents across the dataset are generally more optimistic about their organizational outlook. Perhaps senior leaders have a clearer view of macro-level threats that haven't yet fully translated into operational disruption.

Forecast confidence

Earlier, we saw that growth predictions are strong. But how certain are our respondents in their predictions?

We measure forecast confidence by calculating the standard deviation away from a respondent’s revenue prediction - as a measure of how ‘spread out’ their predictions are.

For Q1 2026, our sample has registered 5.3% uncertainty in their revenue predictions. As the data keeps rolling in, we believe that number will become one of the most important trendlines in future editions of this report.

Geographically the UK registered the highest uncertainty at 5.8%, while Germany came in with the most confident predictions - 4.4%. So the country predicting the highest growth is the least confident in their predictions.

The same picture unfolds when we look across industries: construction (6.2%), retail trade (6.1%) and finance/insurance (6%) have the highest uncertainty of any industries, despite predicting high growth.

AI maturity tracks uncertainty: 4.8% for early stage companies while leaders, who also predict higher growth, are 6.6% uncertain.

Across org sizes there is little separation between small (5.6%), mid-sized (5.4%), and large (5.6%), but enterprise-scale organizations came in far below at 4.1% - illustrating the natural advantages they have in dealing with economic shock, but also perhaps their more advanced forecasting capabilities.

Uncovering the drivers of uncertainty

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So what’s driving this uncertainty creep? Macroeconomic conditions, cost increases and margin pressure, and regulatory or compliance changes are the biggest culprits across the board.

Supply chain is much more of a concern in the US (likely reflecting tariff policy), with 37% reporting it as a driver as opposed to 27%, 25%, and 23% in the UK, Germany, and France respectively.

The US and UK report being less concerned with geopolitical instability than France and Germany, perhaps due to their relative distance from conflicts.

As AI maturity increases, different drivers become more of a concern. Regulation and compliance are a problem for 34.9% at early, versus 48.8% at leading.

The same is true of data quality and, interestingly, pace of technological change - perhaps suggesting companies who’ve invested most into AI have done so out of necessity as their business is disrupted.

But the good news for those companies is that AI maturity does decrease the likelihood of macroeconomic conditions or cost increases and margin pressure being an issue.

Enterprise-level businesses feel macroeconomic pressure the most at 55%, compared to 49–52% across smaller segments. Enterprises also show notably higher concern about geopolitical instability (43%) - 10 points above small businesses (33%) - reflecting their greater exposure to international operations.

Data quality/visibility is most acute for mid-sized businesses (34%), which is interesting - these companies may have outgrown basic tools but lack the data infrastructure of larger organizations.

Run another forecast…

When life throws a curveball, CFOs reforecast. This year, the average business produced a forecast 39 times - that’s over 3x a month.

Geographically the UK forecasted the least, at 33 times, while Germany led the way with 44. Lining these results up with the forecast confidence figures suggests it may be Germany’s frequent forecasting that’s giving them a more confident view into their future.

Split by AI maturity we see that leading AI firms are performing 70 forecasts a year, 40 more than the average and still 31 ahead of advanced firms, who do so 39 times - a clear indication of the potential for AI to increase the strategic role of the finance function.

Part 3: All in on AI

Adoption rates soar

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AI adoption is now mainstream in finance, but the pace of adoption varies sharply by market and sector.

Geographically, France is lagging behind. 24% of French respondents have no AI adoption, compared to 11% in the US and 13% in the UK.

Only 8.3% of French respondents describe their AI use as "mature", the lowest of any geography, and 34% are at the "limited experiments" stage — again the highest of any market.

Germany presents an interesting contrast: despite relatively low AI maturity (14% mature), it has the joint highest proportion planning to implement soon (14%), suggesting it is catching up. The US leads on mature adoption at 17%, consistent with its broader technology investment lead.

AI overtakes automation

Generative AI is officially mainstream: it’s now used in more finance functions than machine learning or traditional automation.

While generative AI is dominant everywhere, adoption actually declines with size at the top end - small (72%) and mid-sized (72%) businesses are ahead of enterprise (65%). Agentic AI remains lower, but we’ll be watching over the coming quarters to see how that figure moves.

This may reflect the enterprise working through governance and procurement hurdles, and indeed agentic AI also shows a notable dip at the enterprise level (29%) versus 35–37% for all other size bands.

But traditional/rule-based automation tells the opposite story - enterprise firms lead at 54% vs. 46–49% elsewhere, consistent with larger organizations having deeper legacy automation investments.

What are you using it for?

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The top use cases across our sample are automating repetitive tasks, auto-generating summaries/reports, and forecasting. Modeling assistance came in lowest - from these figures we can surmise which use cases are the most difficult to automate, for now.

But as AI maturity increases, these use cases unlock. Between early stage and leading firms, there’s a 29% gap on revenue/spend data classification, 24% for auto-generating summaries/reports, and 16% on scenario planning.

These use cases are where the real game-changing value is being derived, so business leaders should take note: investing in AI pays off.

How AI is delivering value?

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Our respondents say productivity and efficiency is the single largest benefit, at 59% of respondents, and only 2% overall say AI has had no measurable impact - clearly, finance is sold on the value of AI.

But productivity and efficiency isn’t the only benefit: analyzing across AI maturity we see an interesting picture. The gap between the benefits realized by early adoption and leading organizations is massive across the board, but we also see large jumps at other maturity levels:

• Quality of decision making shows a huge jump between advanced (50%) and leading (69%) organizations
• Accuracy and confidence in planning outcomes jumps from 35% at developing to 46% at advanced, and then to 56% at leading
• Faster planning cycles shows an 11% increase between advanced and leading organizations

The implication for finance leaders at an earlier stage is important: absence of dramatic results now doesn't mean the investment won’t work. The most valuable benefits come as your AI maturity increases.

Investment accelerates, but the gap widens

79% said AI use increased in the past quarter, and the overall average budget increase planned over the next year is 17%.

The US, the leader in AI, is planning the largest increase in investment at 20%, with the UK coming in just behind at 17%. France and Germany lag at 11% and 12% respectively. While Germany has a high proportion planning to implement soon, they don’t seem to be matching it with investment.

Across industries technology (21.5%), construction (19.7%), and finance/insurance (18.9%) are planning to increase spending the most. Wholesale trade (9.3%), healthcare (11.3%), and retail trade (12%) have the tightest purse strings.

Leading AI maturity firms are investing 30% more than last year, whereas those at early stage are only planning a 7.8% increase. That gap - 22 percentage points - means the distance between these groups isn't going to narrow, it's going to compound.

Part 4: The risks

The forces impeding AI ROI

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Overall, the biggest barriers to success with AI are high costs, data quality, and lack of expertise.

The AI leader, the US, is struggling most with high costs and data quality, but is less burdened with regulatory/compliance issues - which are top concerns for Germany and the UK. France struggles most with lack of internal expertise which would appear to be consistent with its more nascent adoption position

Lack of internal expertise is also at its most acute for small firms, which comes as no surprise. Data quality seems to be at its most troublesome for mid-sized firms. Cultural resistance seems to scale directly with size, with larger organizations struggling more with internal adoption.

A familiar picture on AI emerges between maturity levels: unclear ROI falls as maturity scales, which would imply that leading firms have seen clear results. Data quality issues peak in the middle at 41% for developing orgs, while leading firms seem to have pushed through somewhat at 35%.

Mind the perception gap

An interesting trend has also emerged in the data.

As respondents become more senior, their tendency to identify their organization as more mature with regards to AI implementation increases - dramatically.

We see this perception gap show up in every question from the survey around AI: senior leaders see the impact of AI more favourably, they say they will increase budget for it by larger figures, and they see less barriers to success with it.

This is a real potential problem: if senior leaders believe AI is more embedded than it actually is on the ground, they may be making strategic decisions based on capabilities their teams don't yet have.

Our advice? Leaders need to set up clear, honest feedback channels to ensure that they’re getting the information they need.

Our takeaways and advice

There’s plenty of information for any finance leader in our Q1 findings. But our key takeaways would be:

1. AI maturity is a clear predictor of success‍

Leading firms are achieving better outcomes across the board and reported 12% higher growth in the past year than laggards. On top of that, benefits increase in breadth and intensity as maturity scales. The gap between leaders and laggards seems to be widening.

2. Growth prospects seem fragile‍

Many of the segments predicting high growth in the next year also have the highest level of uncertainty. But we see that with added forecast scenarios, uncertainty decreases. Now would be an excellent time to improve your forecasting and scenario planning capabilities.‍

3. An AI maturity perception gap exists

Leaders may have a warped view of how advanced they are. It’s important that they take the time to understand what’s happening on the ground, because if they don’t they risk missing out on the real benefits that being a leader can hold.

Methodology

All data was collected from 2,000 respondents between 15th January and 19th February 2026 - notably, before major geopolitical developments in March.

That’s all, folks

We’ll see you in June for Q2 figures, which we're anticipating will reflect the seismic geopolitical movements of the past few weeks.

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