A3i™
The challenge
Pharma brand planning is slow, fragmented and disconnected from real-time market dynamics
We’ve simply got used to how broken brand planning is: cross-functional insights are generated in silos, information collection and synthesis remain heavily manual and can take months, and the final plans are created as static annual documents which are often quick to outdate.
The result is ineffective strategy: key signals are missed, decisions are delayed, assumptions are outdated by the time plans are finalised, and strategic choices are rarely stress-tested against competitive, access or market changes.
The solution
It delivers:
- AI-driven multi-source data collection and analysis across internal, external and market inputs. We can build your situation analysis in days.
- Human-led validation, challenge and refinement of AI outputs.
- Brand Plan IQ benchmarking to identify gaps in the final plan versus best-in-class planning standards.
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How it works
Time
Time goes down. Brand plans can be created in 3–4 weeks rather than 4–5 months, as AI accelerates the initial manual information gathering, consolidation and synthesis, moving teams faster into what matters to your brand’s success: strategic debate.
Quality
Quality goes up: more than 30 interdependent AI agents synthesise evidence at scale and generate draft strategic choices for expert human strategist validation and refinement.
The final outputs are then benchmarked using our best-in-class Brand Plan IQ benchmarking tool to further strengthen the final output.
Cost
A3i ultimately delivers higher-quality planning, faster, at a broadly equivalent cost to a standard brand planning process (per brand).
The result is strategic confidence.
Transparent, traceable assumptions and outputs — alongside a living strategy system that updates as the market changes — give teams greater confidence to allocate resources on tactics that are likely to have an impact.
The triple agentic layer
Layer 1: searcher agents
Building a comprehensive situation analysis evidence base.
Layer 1 brings together the information required to build the situation analysis.
Dedicated Searcher Agents gather, organise and process evidence from multiple internal and external sources — including your own market research, advisory board reports, CRM data, clinical evidence, treatment guidelines, epidemiology and competitive intelligence.
Each Searcher Agent is aligned to a specific component of the situation analysis, and trained specifically (for example, competitive intelligence searcher agents are trained in competitive intelligence knowledge and frameworks; Pricing & Market Access searcher agents have Pricing & Market Access training, etc).
To remove any doubt in AI’s outputs, every source and assumption is clearly referenced and fully traceable back to starting source – enabling teams to see where the evidence has come from and distinguish between established facts, interpretations and assumptions.
Step 2 – layer 2: synthesis & analysis agents
Translate evidence into insight, implications and strategic meaning
Each Layer 1 Searcher Agent works in partnership with a corresponding Layer 2 Synthesis & Analysis Agent that analyses the information consolidated by their paired Layer 1 agent.
These Layer 2 agents interrogate the evidence, answer pre-defined contextual strategic questions and translate information into clear findings, implications and hypotheses for each component of the situation analysis.
Layer 2 goes beyond summarising content. It identifies patterns, tensions, evidence gaps, competitive implications and potential changes in customer behaviour that could affect your brand.
The connection between the two layers provides clear source-to-output traceability: teams can follow each conclusion back through the analysis, assumptions and underlying evidence used to generate it.
Step 3 – layer 3: strategiser agents
Connect the full situation analysis and generate strategic choices
Layer 3 agents are designed to analyse Layer 2’s outputs (i.e., across the complete situation analysis rather than analysing individual components in isolation, as per Layer 1 & 2).
Strategiser Agents review the combined outputs from Layer 2 agents to identify the most important cross-cutting themes, strategic tensions and key business issues across your full situation analysis that your end strategy must address.
They assess how market, customer, competitor, clinical and access dynamics interact — ensuring that important signals are not missed within individual workstreams.
Based on this integrated diagnosis, Layer 3 generates a prioritised SWOT and draft directional strategic choices to be subsequently validated by humans in a workshop setting.
The rationale for each choice remains transparent and traceable to the starting source, allowing teams to understand which evidence, implications and assumptions led to each recommendation.
Human validation, activation and benchmarking
Branding Science will then work with your cross functional team collaboratively in a workshop setting to ensure that the final strategy is commercially grounded, strategically specific and capable of guiding meaningful decisions, investment and cross-functional execution.
The final Brand Plan IQ benchmarking step provides an additional quality-assurance layer, identifying gaps against best-in-class planning standards.
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Why branding science
Branding Science are the brand strategy and planning experts. We have worked on hundreds of brand plans, we know what works, and in collaboration with our expert in-house data scientists, we are now applying this expertise to leverage the full power of AI in the brand planning process.
A3i™ is the result of our deep pharma strategy expertise combined with practical AI deployment, giving teams the speed of agentic workflows within a robust governance framework — ensuring data is handled appropriately, compliance standards are respected, and outputs remain grounded in the human contextual judgement, challenge and strategic rigour required for high-quality brand planning.