Leaders across industries are grappling with the implications of AI for their organizations. While some view AI with caution or even fear, forward-thinking executives recognize its transformative potential. But what does it really mean to be an AI-driven organization, and why is it so important for the future of your business?
While digital transformation might already be a familiar concept to many leaders in traditional industries, an AI-powered digital transformation is a complete paradigm shift. Beyond incremental improvements, leveraging the power of AI can help you fundamentally reinvent how your company operates and competes.
In this article, we will explore real-world examples of AI-driven organizations, illustrating how AI helps leaders redesign their companies to scale, create new value propositions, and even reimagine new business models.
Redesigning Operations to Scale Rapidly
In a truly AI-driven company, leaders understand the fundamental value of using data to solve problems and drive decision making. This mindset is embedded in an organization’s core Purpose (Vision, Values, Strategy), as well as in operations. Ultimately, an AI-driven organization is one that is able to systematically turn data into actionable insights, constantly learning and adapting on its own without constant human intervention. Leveraging this power can enable new capabilities, and do so at scale.
Consider these examples of companies from traditional, non-tech industries, at varying phases of AI transformation:
Domino’s Pizza (Food Retailer)
Domino’s Pizza has been piloting its 3Ten project in selected countries, an initiative that aims to have a pizza ready for pickup within 3 minutes or delivered within 10 minutes. AI automatically starts making pizzas before they are even ordered, by using AI to strategically analyze data to predict the moment online customers intend to order. Domino’s is redesigning its operations for unprecedented speed and efficiency, improving customer satisfaction.
Hero MotoCorp (Motorcycle Manufacturing)
Similarly, India-based motorcycle manufacturer Hero MotoCorp uses AI to connect and analyze data from disparate sources: customer feedback, vehicle performance metrics, and assembly lines. This approach gives Hero MotoCorp a self-learning system that identifies design improvements and predicts maintenance needs, streamlining and optimizing operations in real time, while accelerating the launch of new models.
Traditional companies can gain inspiration from software companies, which operate with a centralized insights hub, providing a holistic view of operations, customers, and employees. While digitally native companies may start with this design from inception, traditional organizations can also make the shift. With visionary leadership and a clear roadmap, even the most entrenched giants have made meaningful shifts in their AI-driven journey within three years, ultimately achieving significant AI-driven transformation in five years.
And while established companies may have advantages in resources, networks, and brand recognition, AI can enable smaller, more agile companies to scale rapidly and potentially disrupt larger rivals.
Flexport (Freight Forwarding)
Flexport, founded in 2013, began with founder Ryan Petersen automating tedious paper custom forms, one of several frustrating inefficiencies he encountered in the freight forwarding industry (an industry known for its fragmented systems, data silos, and poor customer experience). Rather than designing his company by function and process, Flexport designed its entire operations around a centralized, AI-powered platform, integrating every step of the shipping journey. The platform connects all stakeholders (importers, exporters, trucking companies, ocean carriers, airlines), enabling them to collaborate seamlessly. It allows the entire organization to gain real-time insights, make data-driven decisions, while offering customers a seamless, end-to-end experience. It has also allowed them to grow and scale rapidly, reaching a valuation of USD $8 billion in 2023, one quarter the valuation of 140+ year-old industry incumbents DB Schenker and Kuehne + Nagel.
Flexport serves as an example of how AI can level the playing field, by reducing the marginal cost of acquiring and serving new customers to near zero, enabling new capabilities at scale. It is a cautionary tale for complacent incumbents, and inspiration for leaders seeking to leverage AI for transformative growth.
Creating New Value Propositions
An AI-driven company is also able to create new value propositions. Consider this example from the agriculture industry:
Charoen Pokphand Foods (Agribusiness)
Thai agribusiness Charoen Pokphand Foods uses AI to analyze weather patterns, satellite imagery, and soil conditions. Previously relying on sheer volume and cost management, their current AI-driven approach optimizes planting times, reduces water usage, and adjusts nutrients. Through precision farming, they reduce the need for broad-spectrum pesticides while increasing crop yields. Ultimately, they are able to leverage the power of AI to create safer, higher-quality products, while promoting sustainability.
Beyond agriculture, AI is also revolutionizing other traditional industries, such as insurance.
Ping An Insurance
Ping An Insurance is a case study in AI-powered reinvention. Founded in 1988, Ping An began as a small, traditional insurance specializing in property and casualty insurance with 13 employees. It has since transformed into a tech-driven financial powerhouse, largely due to its embrace of AI.
For Ping An’s first two decades, it operated as a typical traditional insurer, confined by legacy systems, cumbersome processes, and reactive customer service. But as the Internet expanded in China in the 2000s, its founder Peter Ma sought to transform his business and enable it to compete in the Internet economy. Described as a hyper-learner with an insatiable curiosity, Ma embraced technology aggressively, making significant investments in AI, IT infrastructure, and talent, laying the foundation for Ping An’s transformation.
By systematically using AI to analyze customer data, predict risks, and prevent fraud, Ping An not only streamlined its operations and transformed its culture, but transitioned to a customer-centric strategy. Ping An’s IT developers designed AI-driven software services for institutional clients, individual customers, and their own employees. They went beyond improving existing services, but created entirely new value propositions. Between 2009 and 2014, they introduced innovative offerings like personalized insurance plans, AI-powered investment advisory services, and online healthcare consultations.
Ping An has since become a massive conglomerate with operations in insurance, banking, healthcare, technology, and smart city solutions, creating new revenue streams, positioning itself as a market leader in innovation and customer-centricity, and rapidly ascending the Fortune 500 rankings nearly 300 spots (from 350 to 53) from 2008 to 2024.
Ping An’s transformation shows how AI can catalyze the growth of entirely new value propositions, driving growth even in traditional industries. In regions like Southeast Asia, where many sectors lag in AI adoption despite high digital penetration, the opportunities for AI-powered disruption and innovation are vast.
Reimagining New Business Models
AI also helps companies reimagine their business models. Perhaps the most well-known examples are these companies, of which we would not know or experience in the same way without their AI-powered platform:
- Netflix disrupted video rental and cable television, by creating a personalized streaming experience powered by AI.
- Amazon (Shopee in Southeast Asia) transformed retailing, creating the modern e-commerce industry, using AI to optimize everything from product recommendations to logistics, across millions of products and sellers.
- Uber (Grab in Southeast Asia) disrupted the transportation industry, by using AI to match riders and drivers, and optimizing routes and pricing.
These companies represent early adopters of digital transformation, and pioneers in AI-driven technologies. But their digital origins might make their AI-powered technologies seem less applicable to traditional industries. The real challenge lies in applying AI’s power to industries with a long history of physical processes and tangible products, such as manufacturing. Let’s explore further how AI is reshaping the core of traditional manufacturing.
Haier (Appliance Manufacturer)
Starting in 2012, Haier, the global appliance company based in Qingdao, China, underwent a radical transformation to adapt to the Internet age. Haier’s reinvention centered around three visions: to develop an AI-powered platform-based software-centric business, provide a personalized user experience, and encourage employees to become entrepreneurs.
At the core of Haier’s transformation is its AI-driven data platform. This platform provides teams with real-time insights into customer preferences, market trends, and operations, enabling Haier’s self-managing teams to make intelligent, data-driven decisions quickly, without layers of approval. The platform also connects to eight inter-connected factories which allow mass customization with precision. Haier also developed an ecosystem of partners who also leverage the platform for their respective businesses.
Chairman and CEO of Haier Group Zhang Ruimin explains:
“Our end goal is to have a true connection with our users and create legitimate lifetime value…The platform is the only place for (every Haier) business to go. By eradicating our middle management layer — and laying off more than 10,000 middle-level managers — we have destroyed the original hierarchical structure.”1
Dismantling its hierarchical structure, Haier now has over 4,000 microenterprises of 10-15 people, each focusing on a specific product or market segment. They also streamlined administrative functions, reducing HR staff from 860 to less than 20. While employee count decreased from a high of 130,000 at one point, to approximately 90,000 in 2023 – Haier’s platform helped create more than 2 million jobs among its startup and ecosystem partners.
From their microenterprises, Haier has spun off over 100 independent new startups, with four of these successfully going public. The AI-powered data platform plays a critical role in their growth, enabling them to create lifetime value for their users. Beyond appliances, Haier has extended its portfolio to a wide range of products including gaming laptops, home decoration services, home theaters, wine cellars, real estate, and financing. Successful spin-offs include an e-commerce platform, a healthcare platform, biomedical technology company, and a logistics company, showing the breadth of innovation fostered by Haier’s model. Haier’s transformation shows how AI-driven platforms can act as powerful catalysts, empowering organizations to not just transcend legacy constraints, but unlock entrepreneurship and give birth to entirely new businesses.
A Call to Action
Remember that becoming an AI-driven organization is a journey, not a destination. It requires commitment, investment, and a willingness to fundamentally rethink how your organization operates. Start by aligning your vision, mission, and values with a clear AI strategy. Invest in building a data-centric foundation that empowers your team with insights and autonomy. Enhance your and your senior teams’ knowledge, while developing AI talent at all levels. And lastly, foster and equip a culture ready to create the future.
The companies featured in this article, from Domino’s to Haier, show that AI-driven transformation is not a pipe dream reserved for tech giants. It is a tangible reality that can be achieved. These stories show that AI can help leaders across industries scale, create new value, and even reimagine entire business models.
Ready to embark on your transformation journey? Explore our impact stories and schedule a consultation with us today.
- Zhang Ruimin (Haier) as quoted in “Leading to Become Obsolete,” interviewed by Paul Michelman, MIT Sloan Management Review, June 19, 2017. Link found here.
