By Ma Jinnan
On December 1, 2025, OpenAI and Accenture announced a strategic partnership—a development that could mark the dawn of a new era for AI transformation among European and American enterprises.
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According to the agreement, Accenture will equip tens of thousands of its IT professionals with ChatGPT Enterprise and will serve as OpenAI’s primary partner to help enterprises worldwide adopt and deploy generative AI technologies. This goes beyond a straightforward business deal—it could well be a watershed moment as AI transformation for enterprises in Europe and the US shifts from proof-of-concept to large-scale deployment.
We can see that the partnership actually entails much more than just the technological licensing between two companies. The real goal is to address key obstacles faced by numerous enterprises in the AI era, such as improving transformation efficiency and figuring out how to effectively embed AI technologies into business workflows. Accenture will take on the role of enabler, stepping in for OpenAI to solve these challenges.
This is something we can all sense: although many companies have begun experimenting with generative AI, most still haven't seen a significant boost in business value. Many of the industry-specific scenarios once believed to hold high value have ultimately “stalled at the trial stage”.
The root cause of the slow progress in enterprise AI transformation is that it requires top-level commitment—the deep engagement of senior leadership, who must inspire confidence and make firm commitments across all departments. Many company leaders still tend to view AI transformation as a task for the IT department. In reality, such a fundamental shift is a sweeping overhaul of enterprise strategy, organizational structure, and business processes. The IT department, which typically has limited authority within organizations and frequently faces misunderstanding and challenges from other departments, simply lacks the mandate to drive such a revolutionary change.
In practice, very few business leaders truly understand the technical potential of AI and the complexity of organizational transformation. Only a small number of executives recognize AI as a core strategic priority, while most continue to view it merely as a tool for optimizing existing processes. This perception gap often leads to AI projects being marginalized, making it difficult for them to garner sufficient resources and support internally.
Business leaders often underestimate the challenges of data governance, talent development, and cross-departmental collaboration, while overestimating the short-term problem-solving capabilities of technology itself. The value creation of AI depends on thoroughly refining use cases and reconstructing business closed loops, rather than simply replacing tools. Only when leaders truly engage in strategic alignment, resource allocation, and cultural advocacy can they break down departmental barriers, establish a mechanism for continuous iteration, and drive AI from pilot initiatives to large-scale implementation, unlocking long-term value.
AI transformation requires hybrid, interdisciplinary talents who understand both AI technology and business operations. Such professionals are extremely scarce in the market and require a long training cycle, making it difficult for companies to fill the gap through short-term hiring.
Organizational inertia in large enterprises is also a major obstacle to AI transformation. There are often glaring divisions within companies, with departmental silos hindering AI adoption. Sales, production, and supply chain departments tend to operate independently, causing AI projects to be confined to a single department and making end-to-end business process optimization difficult. For example, while the strategy department may plan for digital transformation, the operations department might persist in traditional practices. Such disconnection means that even technically successful AI projects struggle to gain traction within the organization. Online and offline AI infrastructure may end up gathering dust in a corner, or face resistance from parallel departments after deployment, leading business leaders to feel frustrated or mistakenly believe the impact of AI has been exaggerated.
AI transformation is not only about technological change, but also about fundamentally reshaping workflows and mindsets. Many employees may fear that AI will replace their jobs, which can evolve into resistance against AI-driven transformation.
It is foreseeable that this strategic partnership between OpenAI and Accenture will significantly accelerate AI transformation among European and American enterprises over the next 2-3 years.
From the details of their collaboration, we can see that they are striving to build a mature AI ecosystem by fostering synergy among technology providers, consulting firms, implementation partners, and training institutions. In this way, the barriers to AI adoption will be greatly reduced, and companies will no longer need to build their AI capabilities from scratch.
Leaders of European and American enterprises generally have the willingness and habit to pay consulting firms from different professional fields to help them solve internal management and business issues. In contrast, Chinese business owners tend to be more self-assured and are more inclined to explore solutions independently or rely on their internal teams. They are usually cautious, if not resistant, about bringing in external expertise. This difference in mindset results in Chinese companies often lacking systematic planning during their AI transformation, remaining at the stage of technical pilots and finding it challenging to achieve large-scale effects. At the same time, an excessive pursuit of short-term returns leads decision-makers to hesitate in allocating resources, further delaying the transformation process. This impatient, results-oriented mindset causes many Chinese enterprises to see AI as a panacea, expecting immediate results from any investment. If there is no short-term return, projects are quickly halted. Meanwhile, European and American companies are more willing to invest resources in long-term strategies and accept phases of trial and error and iteration.
China does hold unique advantages in the AI sector: massive data resources, a relatively complete industrial chain, and enormous market capacity. In application innovation, China has also demonstrated remarkable creativity—AI is deeply integrated in e-commerce, social media, and entertainment scenarios. However, this is mostly limited to the B2C consumer internet field, and AI penetration on the industrial side remains significantly low.
Professional consulting firms in China that provide in-depth business process reengineering and strategic transformation services are severely lacking. Professional technical or AI transformation consulting companies are even rarer. In comparison, Europe and the United States have mature management consulting companies such as McKinsey, BCG, and Deloitte, as well as technology consulting giants like Accenture and IBM. This level of specialization allows companies to choose the right consulting partners based on specific needs, greatly reducing the complexity of AI adoption.
According to Accenture’s recent financial report, the company’s revenues related to generative AI (Gen AI) and agentic AI have tripled in fiscal year 2025, and it now has 77,000 AI-trained professionals worldwide. To accelerate its AI transformation, Accenture announced a six-month, $865 million business optimization plan. This plan will involve some workforce reductions and resource reallocation, with the cost savings reinvested into AI-related business development and upskilling employees.
In contrast, most domestic Chinese consulting firms are relatively small in scale and provide a wide range of services, making it difficult for them to establish deep expertise in specific areas. AI consulting requires firms to possess a strong foundation of AI expertise and demands long-term investment in both technology and talent. However, many Chinese consulting companies tend to favor short-term projects and easily commercializable services, which makes it difficult for them to develop core competitiveness in the realm of AI-driven transformation. For example, the recent controversy surrounding "Hua & Hua" illustrates this issue: while their marketing strategy is adept at crafting compelling brand visuals and slogans, it seldom touches on the intelligent restructuring of a company’s operational logic. This approach, though, does cater to business owners who favor short-term results and quick commercialization.
The window of opportunity for AI transformation will not last long. For Chinese enterprises, AI vendors, and local consulting firms alike, now is the optimal time to take collaborative action—allowing professional teams to handle specialized tasks. Otherwise, they risk falling behind in the next wave of technology-driven global competition.
