December 01, 2022
‘PwC sparks intelligence in the digital business.’
PwC announced that it was cited as a Leader in The Forrester Wave™: AI Service Providers, Q4 2022. The Forrester report notes that, ‘AI Service Providers differentiate via strategy and execution.’
Commenting on PwC, the report states that, ‘PwC sparks intelligence in the digital business. The company focuses on business and digital transformation. PwC pushes its New Equation, a multibillion-dollar initiative, to drive substantial business outcomes for clients. AI is a key component for digital success. As evidence of PwC’s commitment to sustained AI outcomes, nearly half of its clients sign on to outcome- and revenue-based pricing (compared to less than 15% for other participants in this Forrester Wave evaluation). Partners are extensive and core to achieving this vision. PwC looks beyond alliances and fosters joint business partnerships and academic relationships for emerging technology and cocreation. The provider also gets credit for its strategy to attract, develop, and retain talent.’
It further notes that, ‘PwC has strong data science and consulting talent. Thirty percent (roughly 12,600 employees) of its data and analytic practice staff are data science and AI experts with advanced degrees. In addition, 85% of the data and analytic staff have completed role-based training in the past year.’
Anand Rao, Global AI Lead; US Innovation Lead, Emerging Technology Group, PwC US, says, ‘We are proud to be recognised as a leader in the Forrester Wave for AI Service Providers. Artificial intelligence and analytics are transforming how business does business. From back-office automation to front office transformation, from changed skills, cultures and ways of working to new go-to-market strategies and business models, AI is everywhere.’
He goes on to say, ‘AI isn’t easy, but PwC’s AI capabilities are helping many companies get it right. Our experienced team and ready-to-go digital accelerators are helping companies with key analytics and AI challenges: developing and assessing strategy, enhancing and monetizing data sets, upskilling talent, building an AI-ready operational model and culture, upgrading technology, creating and maintaining AI models, optimizing potential acquisition strategies and establishing governance and managing risks.’
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