What Strategy& Does

Strategy& is a global strategy consulting business, operating as part of the PwC network. Founded in 2014, the firm advises senior executives and boards of major corporations on their most critical issues, including corporate strategy, digital transformation, mergers and acquisitions, and operational effectiveness. With headquarters in New York and a size band of 1,001-5,000 employees, it leverages PwC's vast resources while maintaining a focus on high-level strategic work. Its consultants analyze complex market data, competitive landscapes, and internal corporate functions to develop actionable plans for growth and innovation.

Why AI Matters at This Scale

For a firm of this size in the knowledge-intensive consulting sector, AI is not a luxury but a strategic imperative for maintaining competitive advantage and scaling expertise. The core product is insight, derived from processing vast amounts of structured and unstructured data. At a scale of thousands of professionals, small efficiency gains in research, analysis, and content creation compound into significant capacity increases and margin improvement. Furthermore, clients increasingly expect their strategy advisors to be at the forefront of technological change, including AI. Adopting AI internally both improves service delivery and creates a foundational experience for advising clients on their own AI journeys. Failure to integrate these tools risks being outpaced by more agile competitors and losing relevance in a market that prizes data-driven decision-making.

Concrete AI Opportunities with ROI Framing

1. Augmented Strategy Development: Implementing AI-powered market simulation tools can reduce the time spent on baseline market analysis and scenario modeling by 40-50%. This directly increases the number of strategic options a team can explore for a client within a fixed project timeline, improving the quality of deliverables and allowing the firm to take on more projects with the same headcount. The ROI manifests in higher revenue per consultant and potentially higher fees for AI-augmented, premium advisory services. 2. Institutional Knowledge Mobilization: A firm with over a decade of projects has a hidden asset in its past reports and analyses. Deploying a secure internal Large Language Model (LLM) as a knowledge assistant can cut the time consultants spend searching for relevant prior art by an estimated 30%. This accelerates onboarding for new hires, improves consistency, and prevents valuable insights from being siloed or forgotten. The ROI is measured in reduced non-billable research hours and increased leverage of existing intellectual property. 3. Intelligent Proposal Generation: The pursuit of new business is costly. AI tools that analyze request for proposal (RFP) documents, match requirements to past successful proposals, and generate tailored outlines and content can improve bid efficiency and quality. A conservative estimate suggests a 15-20% reduction in proposal preparation time and a potential increase in win rates by identifying stronger alignment points. The ROI is clear in higher business development productivity and top-line growth.

Deployment Risks Specific to This Size Band

At the 1,001-5,000 employee scale, deployment risks are magnified by organizational complexity. Integration with Legacy Systems: The firm likely uses a suite of established tools for CRM, document management, and communication (e.g., Salesforce, SharePoint, Teams). Seamlessly integrating new AI capabilities into these workflows without disrupting billable work is a significant technical and change management challenge. Consistent Adoption & Training: Rolling out AI tools across a globally dispersed, partner-led organization requires a robust training program and clear demonstration of value to ensure uniform adoption. Without it, usage will be patchy, and the investment will not realize its full potential. Data Governance at Scale: Ensuring that AI models are trained and operated only on appropriate, non-confidential data is paramount. Establishing and enforcing strict data access and usage policies across thousands of employees and millions of documents requires a centralized, rigorous governance framework to mitigate client confidentiality and compliance risks.