Talent Readiness for Next Generation Data, Analytics, and AI Services PEAK Matrix® Assessment 2025

Enterprises accelerating their adoption of AI and data-driven technologies now face an intensified need for specialized, AI-ready talent to sustain large-scale transformation. Organizations require deep expertise in machine learning, generative AI, Natural Language Processing (NLP), reinforcement learning, MLOps, and AIOps, along with strong foundations in AI ethics, governance, and responsible AI implementation. The rapid pace of technology evolution, widening skill gaps, and growing competition for niche expertise further compound this challenge.

In response, organizations are increasingly partnering with IT and engineering providers that possess mature, future-focused AI talent strategies aligned with the evolving demands of intelligent automation and enterprise AI integration. Providers are proactively investing in AI-focused learning ecosystems, blending traditional upskilling programs with AI-driven personalized learning, internal academies, and project-based training models. They are also prioritizing AI and ML certifications from leading platforms to enhance workforce credibility and deployment readiness. In line with future-of-work principles, providers are embedding AI fluency across roles to enable seamless human-AI collaboration while redesigning talent engagement models to attract and nurture Gen Z professionals through purpose-driven, innovative, and inclusive workplaces. To sustain long-term capability, leading providers are strengthening career development frameworks, promoting continuous learning, and cultivating a culture of experimentation and ethical AI adoption – ensuring a resilient, future-ready workforce capable of driving next-generation transformation.

In this report, we assess 33 IT providers featured on the Talent Readiness for Next-generation Data, Analytics, and AI Services PEAK Matrix^®. The research will help buyers select the right-fit data, analytics, and AI provider for their needs, while data, analytics, and AI providers will be able to benchmark themselves against each other.