Brief
How to Accelerate Progress on AI
How to Accelerate Progress on AI
Our rapid internal deployment offers useful lessons for our clients.
- 2. Oktober 2024
- Min. Lesezeit
- Summarize with Generative AI
Brief
Our rapid internal deployment offers useful lessons for our clients.
A dedicated issue of Time magazine. A massive installation at the Museum of Modern Art. Even a prime-time special hosted by Oprah. No doubt the speed at which artificial intelligence has leaped from technological advance to cultural phenomenon is unprecedented.
But CEOs could be forgiven for experiencing a certain cognitive dissonance regarding these developments, because many businesses today are moving more slowly than they’d like in deploying AI. By now, most company leaders don’t need to be convinced that AI has the potential to transform how work gets done and even how companies are organized. But the challenge of “crossing the chasm” from hype to results requires commitment and innovation.
We know, because we’ve crossed it. At Bain offices around the world, all 18,000 team members have access to AI tools, and 12,000 are actively using them to address in minutes a variety of manual tasks that once took hours or even days. That means they can devote more time to analyzing and applying the strategic insights that deliver real value to clients.
What’s perhaps most remarkable—and instructive—about our journey is how quickly AI has become ubiquitous across our organization.
What’s perhaps most remarkable—and instructive—about our journey is how quickly AI has become ubiquitous across our organization. As one example, within two weeks of making ChatGPT Enterprise available to everyone at Bain, we achieved 60% adoption among our consulting and expert delivery teams.
Yes, two weeks. So it is possible to get results from AI quickly—if you approach deployment the right way. Here are three things we’ve learned that can help boost the velocity of your AI initiatives.
Like most companies exploring the power of AI, we began with pilots. But we designed these pilots to be core to what our teams do. Launching in our Seattle and Washington, DC, offices, we quickly achieved 80% adoption by building ChatGPT Enterprise tools that could produce Python code for data analysis and automate complex Excel processes. Consultants instantly saw the labor-saving value of these tools and how they freed up capacity to deliver differentiated insights.
The success of those pilots prompted our senior leadership team to orchestrate a comprehensive rollout of ChatGPT Enterprise, which, as noted, gained 60% adoption among our consultants in just two weeks. In a sense, this rapid adoption was a two-way street: We provided upskilling via training sessions and resources (see below), while many of our consultants, inspired by the tools’ ease of use, quickly became power users and stepped up to train others and further explore what the tools can do.
Bain employees have used ChatGPT Enterprise to create more than 2,000 MyGPTs customized for specific tasks.
In fact, employee innovation has been a pillar of our success. Our rapid adoption of AI hearkens back to the spread of kaizen across the manufacturing sector, when companies learned that employees on the front lines were best positioned to recommend new ways of working. To date, Bain employees have used ChatGPT Enterprise to create more than 2,000 MyGPTs customized for specific tasks. We’re taking this approach further with our GPT Olympics competition, giving employees across the firm a chance to create custom AI tools, with the top solutions incorporated into our internal Citizen Innovation Marketplace, to facilitate sharing and ongoing iteration.
As useful as pilots are, they often prove difficult to scale because companies don’t address the web of supporting activities essential to broad adoption. We moved quickly from a two-office pilot to a global rollout of ChatGPT Enterprise thanks to a series of carefully orchestrated steps:
A playbook helps leaders focus on a critical facet of AI deployment: organizational readiness.
A playbook helps leaders focus on a critical facet of AI deployment: organizational readiness. We’ve written extensively about the responsible use of AI as well as its talent implications, effects on energy consumption, and many other factors to consider. Because the potential impacts of AI are so wide ranging, every organization—even those with less tech-savvy, analytically focused teams—can speed adoption by addressing operating model issues early in its journey.
The combination of leadership from above and an enthusiastic grassroots embrace of AI at all levels across Bain has played a huge role in driving what we call a “rolling revolution,” as teams within every function use AI to work smarter, not just faster. But no company is an island, and while many of the tools and applications we now use were developed internally, we’ve also benefited from strategic alliances with OpenAI, SAP, and Microsoft. We’re continually refining our roadmap to incorporate their latest AI capabilities and helping our clients do the same.
In addition to our companywide rollout of ChatGPT Enterprise and the launch of our Citizen Innovation Marketplace, we are using 15 distinct AI-powered tools and have more than 100 AI-led innovations in development.
distinct AI-powered tools
AI-led innovations
Some highlights include:
The list is growing every day, as our rolling revolution rolls on. And, as we build and deploy these tools for internal use, we’re capturing all the relevant learning and bringing that knowledge to client engagements in every industry.
Our teams have enthusiastically embraced our growing suite of AI tools and are achieving extraordinary results both internally and for our clients. A spirit of continuous innovation and execution is enabling us to get more value from AI literally every day. We think the three pillars of our success outlined above can help your organization do the same.