This article and the accompanying slide deck kick off a series exploring how companies can adopt the mindset, expertise, and ambition required to win in an AI-first world.
Move over, digital natives. The moment belongs to AI -first companies that have built themselves up from the server floor by spending heavily on tech—and lightly on people. Mercor, for instance, an AI-powered online recruiting site with 30 people on staff, took just two years to reach $50 million in annual recurring revenue. And Cursor, the company whose AI-powered code editor lets you code in plain English, has achieved even more with less, hitting $100 million in annual recurring revenue in a year with fewer than two dozen employees.
Mercor, Cursor, and many other AI-first companies are rewriting the playbook for success. While most companies cannot quickly adopt an AI-first operating model, all companies—even those in
manufacturing
and heavy industry—can prepare for an AI-first future.
The Long Game: What Companies Should Expect
As AI-first companies expand into new areas, traditional companies must rethink their strategies, business and operating models, and talent and tech approaches.
AI is redefining the sources of lasting competitive advantage. Operational scale, large teams, and expensive marketing all lose importance in this new world. Another set of capabilities is emerging to replace them. As AI-generated content spreads, trust, brand, and IP (such as patents, trademarks, and copyrights) rise in importance. So do direct relationships with customers, high-quality data sets, and AI-fluent talent.
Spending shifts from people to tech. Compensation and benefit costs will fall in the aggregate but rise on a per-employee basis because employees will be so highly skilled. Tech spending will rise sharply, while spending in such areas as HR, marketing, and customer support will drop as machines increasingly perform those tasks. The value unlocked by AI will be reinvested.
Increased tech spend redefines the role of IT. IT will maintain the tech, data, and cyber foundation of organizations, but business units will employ tech-savvy talent and have the autonomy to own and deploy AI solutions.
The AI-first operating model rewires how organizations work. Hierarchies will flatten as AI agents— overseen by humans—operate back-office processes. Skepticism about AI will develop into to a full embrace of the speed and adaptability it unlocks.
As AI transforms the workforce, the value of skills and tasks shifts. Work will be organized around lean, elite teams of specialized, well-paid employees. AI will take the toil out of work, enabling high performers to improve productivity and their own enjoyment on the job.
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The Short Game: Tomorrow’s Agenda
Most companies are a long way from becoming AI-first companies. The power of inertia and legacy ways of working is strong, as is the need to keep the trains running. Existing companies are starting on a brownfield, not a greenfield.
Even so, they can start to bend their business to the inevitable: machines increasingly taking on the work of humans. To kick off that transition, companies can develop a set of practices that will set them on the path to being AI-early if not AI-first.
Develop a business-led AI agenda. Define tangible priority outcomes from AI, and ensure that business leaders take ownership.
Embrace AI in your daily work. Use a range of AI tools to increase your proficiency, and lead by example in your teams.
Anticipate the impact on your workforce. Identify where and how roles will shift, and develop a strategy to upskill teams so they can work effectively with AI.
Show impact and scale. Focus on a few high-value initiatives to demonstrate measurable impact and the ability to scale.
Fund what works. Allocate resources to the promising early wins and build a plan to budget for AI investments that deliver value.
At most companies, the transition to AI will take time in the same way that the introduction of every new technology—steam power, electricity, the Internet—has taken time. But time is a wasting asset. The longer companies wait, the more likely their competitors will not.
