What is a Frontier Firm?
A Frontier Firm is a new class of organization that puts AI at the heart of its business strategy to reinvent how it operates, innovates, and augments human capacity at scale. It can be anything from a one-person startup with a multimillion-dollar annual run rate to a large enterprise reinventing itself and how it delivers shareholder value in the age of AI.
Companies participating in the Frontier Firm AI Initiative are cutting-edge leaders who recognize AI as a once-in-a-lifetime opportunity to rethink how their organizations operate. They’re defined by their willingness to take the first steps, to test, to learn, and to share insights that will help shape the next era of business.
Frontier Firms are the ones that show up and choose to participate in rigorous research instead of waiting for the playbook to be written by someone else.
D^3 X Microsoft
The D^3 Frontier Firm AI Initiative aims to deepen understanding and accelerate the practice of building Frontier Firms. Hosted at Harvard Business School in collaboration with Microsoft, this Initiative develops industry-leading research on human-AI collaboration, upskills global C-suite leadership, and delivers new insights and tools to disrupt conventional business thinking.Â
Members collaborate on rigorous experiments with Harvard and Harvard Business School faculty and researchers, as well as Microsoft, to explore AI-first work patterns and functions, starting with Sales, IT, and Finance. They also attend Harvard-led C-suite workshops and learning programs.
The collaboration represents a new model for how academia and industry work together to shape the future of business in the age of AI. We’re creating a living research network that studies how organizations can responsibly, strategically, and effectively embed AI in their core operations.
Early Insights
In an upcoming case from Iavor Bojinov, Raffaella Sadun, and Shunyuan Zhang, this collaboration has already resulted in the following insights:
AI Adoption Requires Structured Experimentation
Unlike standard technology, AI has a broader scope and greater depth of collaboration/automation, requiring a first phase of structured, frontline experimentation to discover new value. Do not assume that employees would self-discover uses without specific guidance. Once experimentation phase is done, it should be followed by adaptation and scaling phases.
Managerial Challenges in Experimentation
Structuring the adoption process involves key managerial challenges: defining what to experiment on (wide enough for discovery, narrow enough for scaling), selecting the right people (who can tolerate uncertainty and short-term unproductiveness), codifying and scaling the learning, and structuring incentives for full-scale adoption.
The Skill-Will 2×2 Framework
Employees’ readiness for AI adoption is categorized by their Skill (digital/AI literacy) and Will (motivation/willingness to adopt):
- High Skill – High Will (“The Evangelists”): Natural early adopters who pioneer new applications.
- High Skill – Low Will (“The Skeptics”): Resist adoption; need framing shifts or incentives. Their conversion can have outsized influence due to their credibility.
- Low Skill – High Will (“The Learners”): Motivated but need structured support (trainings, shared prompts); they are crucial spreaders of established use cases.
- Low Skill – Low Will (“The Resisters”): Laggards who avoid experiments; may not be ideal subjects to involve in experimentation, but need to be brought along when technology use is more certain.
AI Agents Introduce New Dimensions
AI agents exacerbate adoption challenges. They require more substantive onboarding (codifying tacit knowledge, adding a need for “agent management skills”) and create a sharper “winners and losers” dynamic, potentially increasing the performance gap and resistance among employees.