PERSPECTIVE

Pharma's next commercial advantage will come from a connected model

How leaders link data, AI and commercial capabilities to improve performance

5-MINUTE READ

September 22, 2026

In brief

Biopharma leaders agree on where value is created, but investment has yet to catch up. Spending still favors areas where results are easier to measure.
Top performers started earlier, and the lead compounds. Their stronger data foundation makes every new investment more valuable.
Three moves close the gap. Rebalance investment, shift AI toward enterprise decision-making and build talent and operating models as one agenda.

Ask commercial leaders in biopharma what will drive the next decade of growth, and a clear pattern emerges. The advantage is built in the upstream capabilities: in the decisions made long before a product reaches the market, through stronger data, sharper access strategies and more effective launches.

That is not, however, where most of the investments are made.

Investment still flows to marketing and the field, where results are easier to see, measure and defend. This gap, between what leaders say matters and where the funding lands, now separates the companies gaining ground from the ones ceding it.

Yet the greater advantage comes when these upstream capabilities reinforce one another. Better data, for example, improves access decisions, while stronger access planning improves launch execution. And each launch then generates evidence that sharpens the next one. The result is a cumulative advantage that becomes difficult for competitors to close. Turning that potential into durable advantage requires three moves: rebalancing investments, shifting AI to enterprise decision-making and building talent and operating models as one agenda. We explore each below.

This article draws on Accenture’s proprietary longitudinal research, including a performance analysis of 14 leading biopharma companies from 2018 to 2025 and a 2026 survey of 60 commercial leaders benchmarked against 2022. Together, the findings show where commercial investment is shifting and what separates performance leaders from their peers.

Winning over the next few years, I think we need to get our launches right, ensure access is in place, use AI to connect better with customers and maintain our position as pricing and access challenges increase.

Winning over the next few years, I think we need to get our launches right, ensure access is in place, use AI to connect better with customers and maintain our position as pricing and access challenges increase.

Chief Commercial Officer, leading global biopharma company

What the evidence shows

Two dimensions of our research reveal the same pattern. A 2026 survey of 60 commercial leaders, compared with a 2022 baseline, exposes a gap between what they value and where they invest. A separate performance analysis of GlobalData and Evaluate Pharma data of the top 14 biopharma companies tracks actual revenue against analyst forecasts over two periods, 2018 to 2022 and 2023 to 2025. One captures what leaders believe. The other shows what happened. Together, the analyses reveal where commercial advantage is compounding and why some companies are pulling ahead. All percentages stated on this page come from these two sources.

Leaders know where value is moving, but investment has yet to catch up.

When we asked commercial leaders what will drive future success, three capabilities rose to the top: data and analytics at 72%, market access and pricing at 60% and product launch at 48%.

Top-ranked drivers of future commercial success in 2026:

72%

Data and analytics

60%

Market access and pricing

48%

Product launch

But investment tells a different story. The clearest disconnect is in market access and pricing. Although 60% of leaders rank it among the most critical capabilities for future success, just 27% identify it as a current investment priority. Marketing shows the reverse pattern: only 22% rank it among the most critical capabilities, yet 50% identify it as an investment priority (Figure 1).

Figure 1: Investment has yet to catch up with strategic priorities

Capability

Leaders say it’s critical

Actually funded

Market access and pricing

60%

Marketing

22%

50%

AI could widen that gap. As AI budgets take shape, market access and pricing falls further from 27% of current investment priorities to 23% of AI investment priorities. Marketing, meanwhile, remains well ahead at 42% (Figure 2). The pattern points to a familiar organizational bias: investment gravitates toward activities where impact is immediate and measurable, while capabilities that can create advantage over time remain comparatively underfunded.

Access and affordability will increasingly determine success, so we have to get much sharper in how we partner with payers and structure agreements

Access and affordability will increasingly determine success, so we have to get much sharper in how we partner with payers and structure agreements

Commercial VP, leading global biopharma company

Why the leaders keep pulling away

Some of the difference is timing. The companies pulling ahead today began building the capabilities that matter most years earlier and kept investing as their importance grew. In 2022, the eventual leaders were already leaning harder into data and analytics. Four years later, 89% of top performers rank data and analytics as critical, up from 53% in 2022.

“By the end of 2026, AI agents will do the majority of our routine forecasting and customer engagement planning ... Our field team spending 70% of their time on relationship building and strategic selling, versus data and analysis.” — Commercial AI Innovation Lead, global biopharma company.

That early investment creates a reinforcing cycle. Stronger data sharpens decisions. Better decisions improve execution. Each cycle generates new evidence that strengthens the foundations for the next. Other companies are moving in the same direction, but they are starting later and with less focus.

The portfolio analysis shows how that difference is playing out. Across the two periods we studied, three patterns emerge. Two companies held their position among the top performers, and both were already focused on strengthening their data and analytics foundation in 2022. One company moved from the bottom group to the top, then invested more heavily than even the leaders across data, launch, access and customer experience. Three remained in the bottom tier, focused on narrower, more siloed commercial properties.

The analysis is directional rather than causal. Portfolio mix, marketing timing and forecast accuracy also shape performance. Yet the pattern is consistent: stronger performers started connecting these capabilities earlier. As those investments build on one another, the distance between leaders and the rest becomes harder to close (Figure 3).

89%

of top performers today rank data and analytics as critical, compared to 53% in 2022.

(Directional, not causal. With a small set of companies, movement also reflects portfolio mix, market timing and forecast accuracy. The consistent thread is that stronger performers started connecting earlier.)

Figure 4: Where to start depends on where you are today

What leaders should do next

Closing the gap comes down to sharper choices: where the money goes, how the pieces connect and whether the operating model can carry them. Our research and client work show that three moves matter most:

Rebalance investments

The data is clear on those areas where investment is scarce. Market access and pricing ranks second in criticality and receives less than half the investment that its importance implies. This is a significant misalignment. Durable advantage is being left on the table.

Marketing and field engagement are easy to measure and quick to pay back, and that investment is right. Yet differentiation is built elsewhere. The next wave of advantage comes from connecting marketing and field engagement to the upstream capabilities that shape outcomes earlier: access strategy, pricing, launch sequencing, evidence planning, resource allocation and enterprise decision-making.

These are harder to fund and harder to attribute to a single quarter, which is exactly why they remain underfunded relative to their importance, despite being precisely where durable differentiation is created. The mandate is to rebalance and reinvest, sustaining improvement in engagement and marketing execution while directing a greater share of transformation attention toward the capabilities that create structural advantage over time.

Drift is the real risk. Transformation built as one long program assumes the destination stays still. It does not. The leaders separating to the right in the performance data are not the ones with the biggest plan; they are the ones who planned in increments, deployed, learned and re-aimed, so their foundation kept pace instead of aging.

For those starting later, the sequence matters more than the speed. Figure 4 maps where to begin based on where you are today.

Shift AI toward enterprise decision-making

The same pattern from the investment data shows up in AI. Leaders say integration matters, but most are still using AI to automate within the same silos that already exist.

AI is already earning its keep where the case is easier to make, in content, omnichannel and field support. These are sensible starting points, but they automate work inside silos that already exist. The real advantage comes from redesigning the decisions and flows that cross those silos.

The reason: Decision-grade AI requires shared data definitions, integrated workflows and cross-functional agreement on what a good call looks like. Most commercial organizations have none of these at enterprise scale. Unlike automation, enterprise decision-making depends on coordination across functions.

The investment in data and integration pays off here, enabling not just faster execution, but better calls, made earlier, across the whole system. For a deeper look at how AI is reinventing pharma customer engagement in practice, read our perspective on reinventing pharma customer engagement.

Genuine integration remains the exception:

Only 25%

of leaders run field and digital engagement as one integrated system enterprise-wide. In contrast, a majority (58%) have integrated the two only in pockets.

Build talent and the operating model as one agenda

“The organization will need to use data and digital tools to make quicker, smarter decisions while staying close to customer needs. Tight alignment across commercial, medical and access teams will be essential to turn strategy into meaningful impact.” — Chief Commercial Officer, global biopharma company

Our research shows that the three capabilities leaders prize most are adaptability, AI fluency and cross-functional collaboration, in that order. This is fundamentally a people and organizational design agenda.

What the human+AI workforce looks like:

72%

Adaptability

68%

AI fluency

62%

Cross-functional collaboration

People can learn new skills, but their behavior will still be shaped by the way the company is run. If incentives and decision rights continue to reward work within functions, employees have little reason to work across them. Talent and operating model redesign must therefore advance together.

Companies are unlikely to be able to hire all the commercial, digital and data skills they need, either. Few individual people combine these capabilities and as such, most of this expertise may need to be developed internally. The good news is that doing so largely pays off. For example, from our analysis on companies leading in talent reinvention, we discovered that companies that tightly aligned talent strategy with their technology and AI plans achieved revenue growth 1.8 percentage points higher and profit growth 1.4 points greater than their peers.

At the same time, the capabilities that connect these models pay off most when there is genuine specialist depth underneath them. Businesses still need generalists who can connect across commercial, digital and data; companies also need genuine specialists with deep knowledge of each domain, from market access experts to data scientists. The strongest organizations combine both types of workers.

Get the balance right and it compounds like everything else in this model. With each cycle, the team gets sharper and harder to replicate.

Build a connected advantage that compounds

The next commercial advantage in biopharma will come from how well companies connect the capabilities they already know matter. Rebalancing investment strengthens the foundation. Shifting AI toward enterprise decision-making makes that foundation more valuable. Building talent and the operating model together allows the system to learn and improve with every cycle.

That is what makes the advantage difficult to replicate. A competitor can increase an AI budget, hire new talent or invest more heavily in market access. It is much harder to recreate a commercial system in which each investment strengthens the next decision, each decision improves execution and each cycle leaves the organization better prepared for the one that follows.

For companies that started early, that advantage is already compounding. For everyone else, the imperative is to start connecting now.

The authors would like to acknowledge Finn Brauer, Alex Fasolo and Alex Blumberg for their contributions.

Commercial Life Sciences Executive Pulse, Accenture Strategy, conducted April 2022 and June 2026

Accenture analyses of GlobalData and Evaluate Pharma data; April 2022, June 2026

Accenture Talent Reinventors, March 16, 2026.