Mastering Change Resilience: The Key to AI-Driven Success

HBS AI Institute — Mastering change resilience: the key to AI-driven success

TL;DR

An ~870-word summary, published 5 August 2025 by the HBS AI Institute, of a Harvard Business Review article by Karim Lakhani (HBS; the institute’s co-founder and faculty chair), Jen Stave (the institute’s executive director), Doug Ng (its director of design) and Daniel Martines (BCG X): A Guide to Building Change Resilience in the Age of AI (29 July 2025). The argument:

1. The gap is organisational, not technical. “The primary obstacle is the ability of companies to adapt, reinvent, and scale new ways of working. We call this change resilience.” A BCG survey cited in the article finds “just 26% of organizations have achieved value from AI.”
2. The old model was episodic. “You modernized your systems, trained your people, and operated in a stable environment until the next wave of disruption hit.” AI makes that cycle too slow; change has to become a standing competency.
3. Three “muscles”:
   • Sensing — “to pick up weak technological, competitive, or societal signals early.”
   • Rewiring — “the capacity to redeploy talent, data, capital, and decision rights in days or weeks, not fiscal quarters.”
   • Lock-in — “the discipline to codify what a team learns (in process, code, or policy) so the next initiative starts from a higher baseline instead of reinventing the wheel.”
4. Five components of a playbook: Learn (widespread experimentation to shift attitudes and find opportunities), Do (fast initiatives against known deficiencies), Imagine (invent new operating models “instead of duck-taping existing ones”), Act (make the cycle continuous), Care (wellbeing measures against burnout).
5. Exemplars: Shopify, which spun off its logistics arm in 2023 to concentrate on product and built AI-native tools such as Sidekick; and Accenture, DBS, Moderna, P&G and Cisco.

The summary’s own conclusion: the firms with breakthrough AI results “invest in their organization’s capacity to change as aggressively as they invest in AI technology itself.”

Dynamic-capabilities reading

• digital-sensing/digital-scouting — sensing is defined as picking up weak technological, competitive and societal signals early.
• digital-seizing/strategic-agility — rewiring is the cell’s “rapidly reallocating resources” with a time scale attached: talent, data, capital and decision rights moved in days or weeks rather than quarters.
• digital-transforming/redesigning-internal-structures — Imagine asks for new operating models rather than patched old ones, and lock-in codifies what is learned into process, code and policy.
• strategic-renewal/organizational-culture — Learn aims to shift attitudes through widespread experimentation, and Care makes employee wellbeing part of the change programme.

How it connects

• dynamic-capabilities — sensing, rewiring and lock-in line up closely with Teece’s sense, seize and transform and with Warner & Wäger’s digital version. The summary does not cite either. The added emphasis is on speed (days, not quarters) and on codifying learning so it compounds.
• enterprise-ai-adoption — change resilience as the explanation for the gap between AI’s potential and its scale; the 26% figure.
• micro-productivity-trap — Imagine’s “instead of duck-taping existing ones” is the trap’s escape route in one phrase.
• Dumra (DBS) — one of the named exemplars, in its own words.

What was actually ingested

The HBS AI Institute page only, in full. The HBR article it summarises is not in the wiki and was not read, so the framework is known here only through this summary and its quotations. The rendered page drops Doug Ng’s name in two places; it was recovered from the bio image’s filename (see the raw file’s notes:).

Linked entities and concepts

• HBS AI Institute — publisher. Entity created in this ingest.
• Karim Lakhani — lead author of the HBR article summarised. Updated in this ingest.
• Boston Consulting Group — source of the 26% survey figure; Martines is at BCG X.
• dynamic-capabilities, enterprise-ai-adoption, micro-productivity-trap — updated in this ingest.

Dangling (single-source mention, deferred): Jen Stave, Doug Ng, Daniel Martines, Shopify.

Scope and reliability

Secondhand, and promotional in both directions: an institute summarising an article by its own leadership. The framework is a consultancy-style prescription without new evidence; the one number (26% achieving value) is BCG survey data quoted through two layers. Treat the three muscles and five steps as a framing, useful mainly because they map so directly onto dynamic-capabilities theory. Read the HBR original before citing the framework’s details.