What Is AI Next Best Action for Biopharma Commercial Teams?
AI Next Best Action tells biopharma field and omnichannel teams which HCP to engage, how and when. Use cases, KPIs, compliance and how it runs on Databricks.
By Nitya, Solution Marketing, Kasmo Global · Published October 31, 2026
AI Next Best Action (NBA) for biopharma is a decision system that combines healthcare professional (HCP) profiles, prescribing trends and engagement history to recommend the single most relevant next interaction for each HCP: which HCP to engage, through which channel, with which approved content, and when. Kasmo Global Commercial AI Copilot is a governed commercial AI assistant that gives biopharma field teams HCP prioritization, next-best-action recommendations, pre-call briefs and approved-content guidance, built on the Databricks Data + AI Platform.
In short
- AI Next Best Action recommends the next engagement for each HCP across field, email, web and medical channels, based on HCP profile, sales trends and engagement history.
- A Databricks blog on omnichannel NBA reports that companies using NBA have seen HCP engagement improve by 30–40% and sales increase by 4–10%. These are industry-reported figures, not Kasmo Global results.
- Biopharma NBA rests on four connected use cases: Global Customer 360, brand analytics (provider segmentation and sales forecasting), NBA and omnichannel orchestration, and a sales rep and MSL assistant.
- The two KPIs that matter most are HCP engagement uplift and prescription growth, both measured against a control group.
- Kasmo Global Commercial AI Copilot delivers NBA recommendations to biopharma field teams with approved-content, territory and medical-information guardrails.
Why do biopharma commercial teams need AI Next Best Action?
Biopharma commercial teams need AI Next Best Action because HCPs receive a high volume of uncoordinated outreach, and generic, channel-siloed engagement lowers response rates. A Databricks blog on omnichannel NBA notes that an HCP receives an average of nine solicitations a day, much of it poorly timed or irrelevant to that HCP's current needs.
The same source names three root causes that NBA is designed to fix:
- Uncoordinated channels. Field, marketing and medical teams working in silos send the same HCP conflicting or repeated messages.
- Irrelevant content. Messages do not match what the HCP needs at that moment, so engagement drops.
- Poor timing. Outreach misses the window in which the HCP is most likely to respond.
For a brand team, those gaps show up in the two commercial KPIs that matter most: HCP engagement and prescription growth.
How does AI Next Best Action work in biopharma?
AI Next Best Action in biopharma works as four connected layers: a Global Customer 360 that unifies HCP data, brand analytics that segments providers and forecasts sales, an NBA engine that recommends the next action per HCP across channels, and a sales rep and MSL assistant that puts each recommendation in front of the person who acts on it. Every HCP response feeds back into the 360 profile, so recommendations improve over time.
1. Global Customer 360
A Global Customer 360 for biopharma is a single, governed profile of each HCP and healthcare organization (HCO) that combines CRM activity, claims and prescription data, specialty pharmacy data, digital engagement and field interactions. Databricks describes the provider NBA pattern as unifying HCP, claims, CRM and specialty pharmacy data before deploying NBA agents, and Unity Catalog governs access to those profiles by role and territory.
2. Brand analytics: provider segmentation and sales forecasting
Brand analytics for NBA covers provider segmentation, which groups HCPs by prescribing potential, specialty, access and engagement behavior, and sales forecasting, which projects demand by brand, territory and segment. Segmentation tells the NBA engine which HCPs to prioritize; forecasting tells brand leaders where engagement is likely to move prescriptions.
3. Next Best Action recommendations and omnichannel orchestration
The NBA engine scores the possible next actions for each HCP (a rep visit, an approved email, a webinar invite, a medical follow-up) and recommends the one most likely to raise engagement within brand strategy, consent and budget limits. Databricks describes deploying NBA agents with Agent Bricks that recommend channel, message and timing, and its Next Best Action Solution Accelerator plans touchpoint volume and sequence at the HCP level.
4. Sales rep and medical science liaison (MSL) assistant
The rep and MSL assistant is where NBA reaches the field: a pre-call brief for each HCP, the recommended next action with the reason behind it, approved content to use, and a drafted follow-up the rep reviews before sending. Questions that fall outside the approved label are routed to Medical Information rather than answered by the commercial assistant, which keeps the commercial–medical boundary intact.
What results can biopharma expect from AI Next Best Action?
Biopharma companies using AI Next Best Action have reported HCP engagement improvements of 30–40% and sales increases of 4–10%, according to a Databricks blog on omnichannel NBA published April 29, 2025. These are industry-reported ranges, not Kasmo Global results, and actual outcomes depend on the brand, data readiness, field adoption and how the program is measured.
| KPI | What it measures | Industry-reported range | How to measure it |
|---|---|---|---|
| HCP engagement uplift | Change in HCP response: email opens and clicks, accepted calls and meetings, webinar attendance, content interactions | 30–40% improvement | Compare HCPs receiving NBA recommendations with a matched control group over the same period |
| Prescription growth | Change in new-to-brand and total prescriptions for targeted HCPs | 4–10% increase in sales | Test vs. control territories or HCP cohorts, adjusted for seasonality and market access changes |
Measuring against a control group is what turns an NBA pilot from an anecdote into evidence a brand leader or CFO will accept.
What capabilities should a biopharma Next Best Action solution have?
A biopharma Next Best Action solution should have governed HCP data, explainable recommendations, approved-content and compliance guardrails, closed-loop learning, delivery inside the field workflow, and control over AI cost and model choice. Each one maps to one of the four principles Databricks uses for its platform: context, control, cost and choice.
- Governed, unified HCP data (Context). One HCP/HCO profile across CRM, claims, prescription, specialty pharmacy and digital data, with role- and territory-based access in Unity Catalog.
- Explainable recommendations (Context). Each recommended action shows the signals behind it, so reps and brand teams can judge it.
- Approved content and compliance guardrails (Control). Recommendations draw only on current, approved materials; off-label questions route to Medical Information; patient-level data stays out of the field view.
- Closed-loop learning (Control). HCP responses flow back into the models, with monitoring and retraining so recommendations stay accurate.
- Delivery in the field workflow (Context). Recommendations appear where reps and MSLs already work, not in a separate dashboard.
- AI cost control and model choice (Cost, Choice). Unity Gateway sets budgets, rate limits and spend attribution by team and agent, and routes requests across proprietary and open models.
How does Kasmo Global Commercial AI Copilot work with Databricks?
Kasmo Global Commercial AI Copilot runs on the Databricks Data + AI Platform: Lakeflow brings commercial data in, Unity Catalog governs the HCP/HCO 360 and territory access, Agent Bricks hosts the NBA and rep-assistant agents, Genie answers territory and performance questions in plain language, and Unity Gateway controls model access and AI spend. The Copilot then delivers prioritized HCPs, next-best actions, pre-call briefs, approved content and drafted follow-ups to the field team.
| Use case | Databricks Data + AI Platform component | What Kasmo Global Commercial AI Copilot does |
|---|---|---|
| Global Customer 360 | Lakeflow, Unity Catalog | Builds governed HCP/HCO, territory and activity views from CRM, claims and specialty pharmacy data |
| Brand analytics | Lakehouse, AI/BI, Genie | Segments providers, tracks account performance and answers territory questions, limited to each user's territory |
| NBA and omnichannel | Agent Bricks | Combines target tier, account potential, call recency and commercial signals to recommend which HCP needs attention and what to do next |
| Rep and MSL assistant | Agent Bricks, Unity Gateway | Produces pre-call briefs, surfaces approved content with citations and drafts follow-ups the rep reviews and sends |
Agent Bricks. Agent Bricks is an open agent developer platform for building, deploying and optimizing custom agents on any model, framework or harness, with all your data. It is powered by Omnigent, a multi-harness agent development platform, and includes AI search, memory, sandboxing, evaluations, observability and monitoring. Learn more: Agent Bricks product page
Genie One. Databricks Genie is the data-smart AI coworker, giving business users natural-language access to governed enterprise data. Genie One is the coworker experience, Genie Agents are domain-specific agents built on governed data, and Genie Ontology supplies the shared business context all of them draw on. Because Genie runs on Unity Catalog-governed assets, answers respect existing permissions and lineage rather than requiring a separate semantic layer. Learn more: Genie One product page
Unity Gateway. Unity Gateway is the enterprise AI control plane for accessing, managing and optimizing AI across every team, application, model and agent. It provides reliable capacity across leading proprietary and open models through a single gateway, Smart Routing that directs each request to the best-fit model for cost, quality and performance, and budgets, rate limits and spend attribution by user, team, agent and model. Access policies, guardrails and audit trails span models, agents, MCPs and tools. Learn more: Unity Gateway product page
How do biopharma teams keep AI Next Best Action compliant?
Biopharma teams keep AI Next Best Action compliant by limiting recommendations to approved content, separating commercial and medical responses, enforcing territory-based access and keeping patient-level data out of the field experience. Kasmo Global Commercial AI Copilot applies these controls by design:
- Approved content only. Promotional responses are grounded in current, approved assets with source citations; unsupported claims are not generated.
- Commercial–medical firewall. Off-label and beyond-label questions are detected and routed to Medical Information instead of receiving a commercial answer.
- Territory-aware access. Account and performance answers are limited to the HCPs, HCOs and territories each user is authorized to see.
- Patient data protection. Patient-level information stays out of the field view through governed views, aggregation and small-cell suppression.
- Human review. Reps review and send every follow-up; the Copilot drafts, people decide.
Kasmo Global release-tests the Copilot for off-label routing, territory isolation, patient-data suppression, citation validity and answer accuracy.
How do you get started with AI Next Best Action?
Biopharma teams get started with AI Next Best Action by picking one brand and one KPI, confirming the HCP data foundation, defining a control group, piloting in a limited set of territories and expanding once the results hold. Kasmo Global follows this sequence:
- Pick the brand and the KPI. Choose one brand and decide whether the pilot targets HCP engagement uplift, prescription growth, or both.
- Assess the Customer 360. Check that CRM, claims, prescription and specialty pharmacy data can be unified and governed in Unity Catalog. If the foundation is not ready, see our guide to the Databricks lakehouse for biopharma commercial.
- Define the control group. Match test and control HCPs or territories before launch so results are attributable.
- Pilot in the field workflow. Deploy Kasmo Global Commercial AI Copilot to a limited set of territories with guardrails switched on from day one.
- Measure and expand. Compare engagement and prescriptions against control, then extend to more brands, territories and channels.
Ready to see where Next Best Action would move your brand's numbers? Book an AI assessment with Kasmo Global, or explore how we support pharmaceutical companies.
Frequently asked questions
What is Next Best Action in pharma?
Next Best Action (NBA) in pharma is an AI approach that recommends the single most relevant next interaction for each healthcare professional, including the channel, the approved content and the timing, based on the HCP's profile, prescribing trends and engagement history.
How is Next Best Action different from omnichannel marketing?
Omnichannel marketing coordinates messages across channels; Next Best Action is the decision layer that chooses which channel, message and moment to use for each individual HCP. Omnichannel without NBA follows a fixed plan; omnichannel with NBA adjusts to each HCP's responses.
What data does a biopharma Next Best Action model need?
A biopharma Next Best Action model needs HCP and HCO profile data, CRM call and email activity, claims and prescription data, specialty pharmacy data, digital engagement history, consent to contact, and the brand's approved content and business rules.
How much can Next Best Action improve HCP engagement?
A Databricks blog on omnichannel NBA reports that companies using Next Best Action have seen HCP engagement improve by 30–40% and sales increase by 4–10%. Results vary by brand, data quality and field adoption, so teams should measure against a control group.
Does Next Best Action replace sales reps or MSLs?
No. Next Best Action recommends what to do next; sales reps and medical science liaisons decide and act. In Kasmo Global Commercial AI Copilot, reps review and send every follow-up, and medical questions route to Medical Information.
How does Next Best Action stay compliant with promotional rules?
Next Best Action stays compliant when recommendations use only approved, current content with citations, off-label questions route to Medical Information, access follows territory permissions, and patient-level data stays out of the field view. Kasmo Global Commercial AI Copilot applies all four controls.
Why run Next Best Action on the Databricks Data + AI Platform?
Running Next Best Action on the Databricks Data + AI Platform keeps the HCP 360, the models and the agents on one governed copy of the data: Unity Catalog governs access, Agent Bricks builds and monitors the NBA agents, Genie answers plain-language questions, and Unity Gateway controls model access and AI spend.
What is Kasmo Global Commercial AI Copilot?
Kasmo Global Commercial AI Copilot is a governed commercial AI assistant for biopharma field teams that brings HCP/HCO context, territory signals, commercial data and approved content into one place for HCP prioritization, next-best-action recommendations, call preparation and follow-up, built on the Databricks Data + AI Platform.
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