As companies move from AI pilots toward enterprise-wide transformation, EY US is changing how it packages its consulting and technology capabilities. The firm has introduced an Integrated Solutions model that combines AI platforms, proprietary data, industry expertise, managed services and cross-functional teams around specific enterprise problems.
The enterprise AI market is entering a more demanding phase. Companies are no longer asking only how to experiment with generative AI; boards and C-suites increasingly want to know how the technology can change operating models, create revenue and produce measurable financial results.
That shift is prompting professional services firms to rethink how they sell and deliver transformation.
Ernst & Young LLP (EY US) has announced a new Integrated Solutions approach that brings together its consulting, technology, data, AI, risk, tax, strategy and managed-services capabilities around complex enterprise problems.
Rather than organizing the proposition primarily around individual corporate functions, EY says its solutions will combine cross-functional teams, AI platforms, proprietary data and methodologies to deliver end-to-end transformations.
The strategy places AI at the center of the firm’s broader enterprise services portfolio while attempting to address one of the biggest barriers to large-scale AI adoption: organizations rarely operate in neat functional silos.
Moving beyond the AI pilot
Generative AI adoption has expanded rapidly across enterprises, but scaling AI from individual experiments into production remains difficult.
A 2025 McKinsey global survey found that 88% of respondents said their organizations regularly use AI in at least one business function, while most were still working to scale AI beyond individual use cases.
That creates an opening for firms that can connect technology deployment with business transformation.
EY’s Integrated Solutions portfolio is organized into five broad categories: enterprise trust; growth and M&A; productivity and technology; business and operations; and finance.
The structure is designed to reflect problems that cut across traditional organizational boundaries.
For example, an AI transformation can simultaneously involve technology infrastructure, cybersecurity, employee processes, finance, governance and customer operations. Treating those as independent projects can create integration problems that undermine the overall initiative.
EY is instead positioning the integrated model as a way to coordinate those capabilities around an outcome.
Trust becomes an AI infrastructure issue
One of the firm’s offerings focuses specifically on enterprise trust, combining responsible AI, cybersecurity, privacy and risk management.
That reflects an increasingly important reality for enterprise AI: deploying a model is only one component of putting AI into production.
Organizations also need controls around data access, security, regulatory compliance, model behavior and accountability. Those requirements become particularly significant in industries such as financial services, healthcare, manufacturing and energy.
EY’s proposed trust solution is intended to bring those controls into a unified operating model rather than treating AI governance as a separate compliance exercise.
That approach aligns with the broader enterprise movement toward AI governance frameworks that are integrated into technology and business processes from the beginning.
AI is reshaping the consulting market
EY is not operating in isolation.
Accenture, Deloitte, PwC and KPMG have all been expanding AI-focused consulting, technology implementation and managed services as customers look for help moving from experimentation to production.
Meanwhile, technology companies including Microsoft, SAP, Salesforce and IBM are embedding AI into enterprise applications and cloud platforms.
This creates an increasingly competitive market in which traditional consulting firms are no longer competing solely on strategy expertise. They also need technology platforms, implementation capabilities, proprietary data and ecosystem partnerships.
EY’s model reflects that convergence.
The firm says its Integrated Solutions will be supported by ey.ai The Reimagination Engine, an AI-led system designed to help clients implement AI across their businesses.
The company’s partnerships also extend the model into major enterprise technology ecosystems. One growth solution, for example, is being developed with Microsoft, SAP and other AI organizations to connect parts and service operations and support new revenue opportunities.
From disconnected data to industrial intelligence
Another example illustrates how EY is attempting to combine AI with operational transformation.
The firm’s business and operations solution for financial services, manufacturing and supply chains is designed to replace disconnected data silos with an AI-driven operational model.
The solution incorporates technology from SymphonyAI, which says its industrial AI platform has been trained on more than 3 million data points from more than 80,000 assets.
The significance is less about the raw volume of training data than the direction of enterprise AI deployment.
Industrial organizations increasingly want AI systems that can work with operational data, identify patterns and support decisions within real-world environments. That requires integration with existing assets, systems and processes rather than a standalone chatbot.
The same principle applies across the enterprise.
The human operating model still matters
EY is also emphasizing leadership alongside technology.
Through its Center for Executive Leadership, the firm is investing in programs designed to help executives navigate operating-model design, governance, economics and leadership behaviors. The programs include collaborations with institutions such as Columbia University, MIT and INSEAD.
That is significant because AI transformation changes more than software.
Companies adopting AI at scale may need to redesign jobs, decision rights, governance structures, incentives and performance metrics. They also need executives who can determine where autonomous systems should be trusted and where human oversight remains essential.
In that sense, EY’s Integrated Solutions strategy reflects a broader evolution in enterprise AI services: technology deployment is becoming inseparable from organizational transformation.
The real test will be measurable outcomes
EY’s announcement comes at a time when enterprises are becoming more selective about AI spending.
The initial excitement around generative AI created a large market for pilots and experimentation. The next stage is likely to be judged by whether those investments improve productivity, generate revenue, reduce risk or strengthen resilience.
EY Americas and US Managing Partner Dante D’Egidio described the shift as a move toward creating new value rather than simply executing existing strategies more effectively.
That ambition puts pressure on EY and its competitors to demonstrate tangible results.
For enterprise buyers, the Integrated Solutions model offers a potential alternative to assembling separate strategy consultants, systems integrators, AI specialists and risk advisers. The tradeoff is that a more integrated engagement can also increase dependence on a single services provider.
Ultimately, EY’s strategy will be measured not by how many AI capabilities it bundles together, but by whether those combinations help organizations move AI from isolated demonstrations into repeatable, governed and economically valuable enterprise operations.
Market Landscape
The professional services industry is undergoing a structural shift as AI consulting, cloud implementation, data engineering and managed services converge.
Traditional consulting models often separated strategy, technology implementation, risk and operational transformation. Enterprise AI increasingly cuts across all four.
EY’s Integrated Solutions strategy puts it in direct competition with firms such as Accenture, Deloitte, PwC and KPMG, while also depending on ecosystems built by Microsoft, SAP and other technology vendors.
The most important market shift is the movement from AI experimentation to production. Companies increasingly need partners that can address data foundations, AI models, cybersecurity, governance, workflow redesign and workforce adoption as a single transformation program.
That creates an opportunity for professional services firms with broad enterprise relationships—but it also raises the bar for proving ROI.
Top Insights
- EY US is reorganizing enterprise services around Integrated Solutions, combining AI, data, technology, risk and domain expertise to address complex cross-functional business problems.
- The model targets the gap between AI pilots and production, helping enterprises connect technology investments with operating-model changes, governance and measurable business outcomes.
- Enterprise trust becomes central to AI transformation, with EY combining responsible AI, cybersecurity, privacy and risk management into a unified approach.
- Microsoft and SAP partnerships expand EY’s technology ecosystem, while SymphonyAI supports industrial intelligence initiatives spanning manufacturing, supply chains and financial services.
- Leadership remains a critical part of AI adoption, with EY investing in executive programs focused on governance, economics, operating models and organizational behavior.
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