Introduction
In today’s corporate digital transformation landscape, “AI-first company” is emerging as a term that deserves real attention, not just another consultant’s buzzword. But can an incumbent truly transform to become AI-first, as Intuit is attempting, or must it be designed that way from inception, like Tesla? In my previous article, I defined the AI-first business process and contrasted it with AI-enhanced processes. This piece builds on that foundation to define what an AI-first company is, describe its defining characteristics, and provide examples of corporations undergoing this transformation.
AI-first is a company that centers its operations around AI, as opposed to a company that only occasionally incorporates AI into its operations. The decision-making, business processes, and team structures of the AI-first company are all driven by AI. Its employees work as AI agent orchestrators and feedback providers, and its systems adapt in real time. In AI-first companies, AI influences product development, enhances customer experiences, and impacts the overall business model. These companies are built from the ground up or undergo a complete transformation to become AI-first.
We expect AI-first companies to improve all their operational metrics. Their teams are smaller, and value is measured by how quickly insights from continuously analyzed data are turned into action.
Example AI-First Companies
We see this transformation not just among high-tech companies like Google, NVIDIA, or OpenAI, where technology is the product itself, but also among what we call tech-forward companies. These incumbents use technology as a differentiator, aggressively investing, building, acquiring, and adopting cutting-edge capabilities to reimagine their core businesses, which are in a non-tech sector (finance, retail, logistics, consumer goods, manufacturing, healthcare, etc.).
We have identified several tech-forward companies (Table 1 provides a sample) that are transforming to become AI-first. These companies are rethinking their processes, culture, and customer experience. They have moved beyond AI pilots and now deploy production AI systems, are retraining their staff, redefining governance, and viewing AI as a strategic asset rather than just an outsourced feature. This shows us that real AI success demands integrating culture, people, and business processes, not just technology and data.
|
Company |
AI-first Transformations |
|
Intuit |
Reimagined core processes (e.g., TurboTax and QuickBooks), uses generative AI in customer and advisor interactions, a continuous experimentation mindset, internally developed AI platform. |
|
Tesla |
AI-first products, manufacturing processes, and customer experiences. |
|
Visa |
AI-first approach in every business line and business processes, including fraud detection, payment authorization, and real-time analytics. |
|
JPMorgan Chase |
AI-first transformation of business processes, including risk, compliance, and trading. Generative AI-based new customer experience for wealth management. |
|
Morgan Stanley |
AI-first transformation of its advisory and wealth management business lines. |
|
Walmart |
AI-first transformation of its business processes, including supply chain management, pricing, and inventory management. Use of generative AI in customer experiences. Integrated copilots into employee workflows. |
|
GE HealthCare |
AI-first transformation of clinical imaging, diagnostics, and device operation. Reinvention of both products and services. |
|
Schneider Electric |
AI-first transformation in product design and internal operations (e.g., demand forecasting). |
|
Siemens |
AI-first transformation of its cyber-physical systems business. |
|
Procter & Gamble |
AI-first transformation of the product R&D, manufacturing, and marketing business processes. Internally developed AI platform. |
|
American Express |
AI-first approach in business processes, including fraud detection, customer experience, and credit underwriting. |
Table 1: A small sample of AI-first companies
AI-First Company Characteristics
As mentioned in the previous article, we developed a methodology through which companies transform to become AI-first. Our methodology is based on the characteristics that define an AI-first company:
- Culture and strategy
- People
- Business process
- Technology
- Data and knowledge
Table 2 maps these characteristics to real companies, showing how each one exemplifies different aspects of the AI-first transformation.
|
AI-First Company Characteristic |
Companies Exhibiting It |
| Establish culture and strategies around continuous experimentation and customer centricity that drive ongoing learning, and value exchange between the company and its customers. (Category 1) | Intuit, Tesla, ServiceNow, JP Morgan, Morgan Stanley |
| Define the problems worth solving, engage employees and AI to solve them, and iterate rapidly while promoting agility and adaptability (Category 1) | Intuit, Tesla, ServiceNow |
| Break organizational silos and establish inter-departmental partnerships so that they can quickly turn into action insights from continuously analyzed data torrents. (Category 2) | Intuit, JPMorgan Chase, Morgan Stanley, GE HealthCare, Schneider Electric, Siemens, Walmart |
| New and existing employees embrace AI. They contribute to and create AI innovations. (Category 2) | Intuit, ServiceNow, JPMorgan Chase, Morgan Stanley, Walmart, Siemens, Schneider Electric |
| Redesign processes from the ground up with AI at their core and feedback loops that can support iterative refinement (Category 3) | Intuit, Tesla, ServiceNow, Morgan Stanley, Siemens |
| Define, implement, and monitor metrics to assess the effectiveness of each AI-first business process. (Category 3) | Intuit, ServiceNow, JPMorgan Chase |
| Spend years experimenting with AI technologies and view data and AI models as key corporate IP. (Category 4) | Tesla, JP Morgan, Morgan Stanley, Intuit, Siemens, ServiceNow |
| Center the system architectures around AI models, enabling composability, retraining, and real-time inference. (Category 4) | Intuit, Tesla, ServiceNow |
| Establish ethics guardrails and develop tools and policies to detect, explain, and mitigate AI-generated inaccuracies and protect data privacy. (Category 4) | Intuit, ServiceNow, JPMorgan Chase, Morgan Stanley, GE HealthCare, Siemens, Visa, American Express |
| Develop or adopt systems that integrate structured and unstructured data, making them available to AI models. | Intuit, Tesla, ServiceNow, JPMorgan Chase, Morgan Stanley, Walmart, Siemens |
| Integrate AI model development, deployment, monitoring, and governance. (Category 4) | Intuit, Tesla, ServiceNow, JPMorgan Chase |
| Treat data as a strategic asset essential to competitive differentiation and invest in scalable and real-time data infrastructure. (Category 5) | Intuit, Tesla, ServiceNow, Visa, American Express, JPMorgan Chase, Morgan Stanley, Walmart, Siemens |
Table 2: The characteristics of AI-first companies
In my book The Flagship Experience, I provide a blueprint of how automakers and their Tier 1 suppliers can use the transition to software-defined new energy vehicles to transform into AI-first companies and provide a new end-to-end customer experience. I describe the culture and people changes that will need to be adopted and how business processes will need to be redesigned. Incumbent automakers have embraced AI as an adjunct to their existing processes, rather than placing it at the core of redesigned processes. As a result, data and AI models, and by extension, software, are still not treated as key IP assets.
Conclusion
Becoming AI-first is no longer optional for companies that want to maintain a competitive edge in the age of discriminative and generative AI and continuous digital reinvention. The AI-first transformation requires reimagining not just processes and technology stacks but also culture, talent models, and governance frameworks. The companies that undertake this transformation will define their plan and timeline to execute it. The examples shared here prove that even large incumbents can reinvent themselves if they treat data and AI as strategic assets and fully integrate them into every facet of their business.
Next related post