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Which companies have the greatest potential to transform and grow in the age of AI, displacing incumbents? We developed a data-driven model to find out.
As technology has accelerated, so has the upheaval in the S&P 500. In the 1970s, the average lifespan of our largest companies was close to 40 years. Now it’s under 20.
With generative AI, things are only going to change faster. Companies that keep pace, adapt, and leverage their data to the fullest will most likely succeed. Those that don’t will face existential threats. Historically, technological revolutions like personal computing, the internet, and cloud computing have catalyzed profound shifts in the corporate landscape, causing significant turnover within the S&P 500.
So, which companies have the highest potential to transform and grow in the age of AI, replacing incumbents?
We analyzed leading mid-cap companies to identify the 50 with the most to gain from generative AI. These companies are often more agile than their larger counterparts. They’re more likely to swiftly adapt and integrate AI-driven innovations, optimize their operations, and create new value propositions. This adaptability, coupled with their ability to harness first-party data as a competitive moat, positions them to capitalize on AI's transformative potential—outpacing slower, more entrenched competitors while maintaining a competitive advantage against upstarts.
Methodology
We evaluated the potential for generative AI transformation among large, public, non-AI US companies with under $5B in revenue. Our assessment used five criteria:
- Revenue to Employee Ratio (R/E): Lower ratios suggest higher potential for AI-driven efficiency gains.
- Operating Margin (OM): Lower margins indicate more room for improvement through AI.
- Cash and Cash Equivalents (C): More cash on hand suggests greater ability to invest in AI.
- Industry Weight (IW): Based on experience, case studies, and research, we determined specific industries (e.g., healthcare, finance) are more primed for rapid AI adoption.
- X-Factor (XF): Qualitative analysis of existing AI initiatives and leadership stance on AI.
Companies were scored 1-5 on each criterion, then evaluated using a weighted formula. Higher scores indicate greater potential for AI transformation. Data was sourced from Zoominfo, SEC 10K filings, and Yahoo Finance.
A perfect score of 5 (which only one company achieved) would indicate that the company has great potential to be transformed by generative AI. A score of 3 might indicate several things: the company may already operate so efficiently that automating certain roles won’t dramatically impact the bottom line. Or maybe they just don’t have enough cash on hand to invest in new technology meaningfully.
We disqualified companies within our parameters if they had too few employees to be meaningfully considered (like certain super small investment firms), and we included a potential generative AI use case for each company based on our analysis.
What may be holding these companies back from AI transformation?
Over the past 20 months, since ChatGPT launched generative AI over the tipping point and into the cultural and corporate zeitgeist, we’ve held discussions with corporate leaders about their generative AI strategy.
While early 2023 treated us to breathless speculation about the rapid pace at which GenAI would transform the corporate world, the truth is that most organizations are just now coalescing around a GenAI strategy and moving past the pilot phase.
There’s no roadmap here, and one of the biggest barriers has been talent. Seventy-nine percent of leaders believe their company needs to adopt AI to stay competitive, and enterprise organizations rank a lack of strategy and talent with the appropriate skillset as their biggest barrier to transformation in this new age. This, in part, is why we’ve seen such heavy demand for the A.Team model, which gives companies access to top, independent AI specialists who have overseen AI strategies and implementations across myriad industries over the last two years, and can mitigate common mistakes. Once a strategy is in place, companies then get access to full product and engineering teams — not all of whom need to be AI experts — to rapidly prototype and scale new solutions.
While GenAI may be creeping into a trough of disillusionment, we expect companies who bring on the right strategic and technical expertise to apply this technology to business use cases to quickly escape it — and gain a huge advantage over the competition.
The AI Future 50
- CrowdStrike
Industry: Software
Transformation Score: 5
CrowdStrike made the news in July when a software update crashed much of the global tech infrastructure; in a time of chaos and introspection, they also rank at the top of our rankings as the only company to earn a perfect store. They have a low revenue-to-employee ratio of approximately $375k, and with $3.4B of cash on hand, they are well-positioned to invest in generative AI. In fact, CrowdStrike has already launched several generative AI initiatives.
Current Challenges: Increasingly sophisticated cyber threats, high competition, and the need for rapid incident response. Low trust following the software update incident.
Potential GenAI Use Case: Automated Threat Simulation and Response. An AI tool that generates simulated cyber threats to train defense mechanisms and automates incident response workflows. This reduces manual intervention, enabling faster containment and remediation of security incidents across the Falcon Data Protection platform.
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