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AI & Data
AI is no longer just a technology. At PwC, we believe that AI is intrinsic to every facet of the business — both our own and our clients. As AI rapidly becomes a natural part of how businesses operate, compete and grow, it will bring disruption to every industry. Our AI teams help clients define what success looks like, reimagine business models and build AI solutions at scale, so they can innovate faster, improve decision-making, and deliver new offerings to market with speed and precision. And we help clients do it all, responsibly.
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Employee Reviews
When asked in an interview with Atlantic Rethink what could happen in the workforce due to AI, U.S. Chief AI Officer Dan Priest said:
“I think humans will become better humans because of AI. That's my prediction. We still need relationships. We still are the decision makers. We are still driving the strategy. And all of those things require us to be good partners and teammates to each other. And so AI actually incentivizes us to get really good at being good humans.”
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Cross Financial Corp. (Cross Insurance) is an industry-leading insurance broker that offers coverage solutions for individuals and businesses. PwC helped the team at Cross Insurance address the labor-intensive task of transferring plan benefits and rates from documents its insurance partners generate into its sales management system. By integrating AI into a document data extraction solution that is embedded within Salesforce, PwC helped streamline the sales process, saving time, improving accuracy and enabling Cross Insurance to deliver quotes faster than ever.
The United Services Automobile Association (USAA) is a financial services company providing multi-line insurance and banking products to members of the military, veterans and their families. Looking to update its financial system and enhance accounting and reporting, the association selected PwC for help implementing Oracle Cloud. As a result, USAA improved its systems, processes, collaboration and cost management with a trusted, connected cloud solution.
What People Are Saying About PwC
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Learning & Development: Learning programs, certifications, mentoring, and hands-on client work are emphasized in AI & Data, with the Learning Collective integrating AI skills and human skills into real projects. This environment appears to accelerate practical growth in enterprise AI, data engineering, and implementation.
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Career Growth: Exposure to large-scale, cross-industry problems and client-facing delivery is highlighted as a strong springboard for building applied AI and consulting capabilities. Early-career professionals in AI & Data are often positioned to gain resume-building experience through enterprise implementations and emerging technologies.
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Team Support: Multidisciplinary teaming is emphasized, with engineers, data scientists, and AI specialists collaborating and sharing knowledge on technically demanding, client-facing work. Mentoring and peer support are highlighted as part of development in these teams.
What People Are Saying About PwC
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Learning & Development: Feedback suggests employees have access to structured AI upskilling through the Learning Collective, certifications, coaching, and learning embedded in real client work. Hands-on delivery across data platforms, AI implementation, and governance appears to reinforce continuous skill growth.
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Team Support: Colleagues are described as multidisciplinary and collaborative, with knowledge-sharing and mentorship helping people deliver on technically demanding, client-facing projects. Feedback suggests teaming across engineers, data scientists, consultants, risk, and industry specialists is a core part of how work gets done.
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Career Growth: Exposure to large-scale enterprise problems and varied industries is seen as a springboard for developing both technical and client-facing skills. Feedback suggests structured pathways and visibility into complex engagements support advancement for AI & Data professionals.
Recently posted jobs
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Leads operational due diligence workstreams for consumer markets transactions, evaluating operating models, performance, processes, risks, and value drivers. Manages project timelines, budgets, deliverables, and client relationships; analyzes financial statements, market trends, and scenarios; develops acquisition and integration insights; reviews team work; coaches junior staff; and applies digital and AI-enabled tools to improve diligence delivery.
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Lead healthcare provider clinical operations consulting workstreams focused on workflow redesign, patient access, utilization, capacity, service line performance, and technology integration. Analyze operational data, develop recommendations, coordinate engagement activities, manage deliverables, build client relationships, support Epic and Cerner implementations, and mentor junior team members.
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Supports healthcare provider technology consulting engagements by analyzing business processes, assisting with application implementation and testing, validating data flows, documenting issues, preparing training materials, and helping clients improve revenue cycle, scheduling, administrative, and workforce operations.
At a glance
forming responsible ai practices
To address generative AI’s most important risks, PwC’s Responsible AI framework covers strategy, controls, responsible practices and core practices. It can be specially tailored to address GenAI’s greatest potential risks, including biased, offensive or misleading content; new challenges to interpretability; new cyber and privacy threats; and “hallucinations” that threaten performance.
As AI becomes intrinsic to operations and market offerings, companies will need systematic, transparent approaches to confirming sustained value from their AI investments. They’ll also need to manage the risks of large-scale deployment. Rigorous assessment and validation of AI risk management practices and controls will become nonnegotiable.
leading sustainable ai
AI can help companies meet their sustainability goals — if they take the right approach. AI leaders at PwC believe there is reason to be optimistic about AI’s potential impact in creating a sustainable future.
“We’ve been trying the same things, and we haven’t been doing a great job around the environment,” said U.S. and Global Chief AI Engineering Officer Scott Likens in a podcast interview by Atlantic Rethink. “The difference now is AI is accessible by all humans, because it’s such a simple interface. We’ve broken through that barrier of just having it in the research lab, and the scientists programming know how to use it, but no one else does. Now everyone is actually seeing some of the benefits.”
guiding client's ai strategy
“We're really excited about this demo-to-adoption shift from prove-it-to-scale-it,” Chief AI Officer Dan Priest said in a podcast interview produced by Atlantic Rethink. “We're seeing a ton of companies change their thinking. … I love the fact that we're talking about strategy, the future of the business and how work will be done — how I’m going to compete and win in a market. And I think the companies who think about their businesses strategically and they’ve got the foresight and the insight that helps them create sustainable advantage in the market — those are the winners. Those are great conversations to have.”
investing in generative ai
At PwC, we know firsthand how to deploy generative AI at scale and manage the new risks it can bring. With the help of a three-year, $1 billion investment, we’re rolling out GenAI throughout our firm and helping our clients do the same.
Our team members can also use pre-built toolkits with ready-to-use software code and prompts, both internally at PwC and with clients. These toolkits can help speed up the deployment and reduce the costs of GenAI for things like personalized customer experiences, content creation, research, agile software delivery, support services, report generation, deep retrieval, smart summaries and Q&A engines.
