Digital transformation drives growth, efficiency, enhanced experiences, and competitive advantages by evolving business models amid rapid advances in technology, data, and AI that reshape customer expectations and market opportunities. CIOs face ongoing challenges from technological shifts and global disruptions that demand revisiting digital strategies biannually—2020 saw the pandemic, 2022 brought recession concerns, and 2024 marks the rise of generative AI. Two years ago, I discussed generative AI’s effects on priorities like data strategies, customer support, and AI governance. Last year, I focused on generating business value beyond productivity from generative AI. Other analyses covered its influence on the future of work, essential AI investments, and business-impacting opportunities. While previous advice centered on how generative AI shifts digital strategies and priorities, here I explore its impact on organizational models that execute these strategies. Siva Ganesan, head of AI and data at TCS, envisions the next transformational era as one where businesses enhance human capabilities with agentic, generative, and predictive AI. Organizations are building architectures supporting intelligent decisions and augmenting people—not just automating tasks—thereby transforming entire value chains. CIOs should harness emerging AI capabilities to build intelligent organizations by focusing on three key areas: renewing the focus on customer centricity, evolving business engagement, and refining digital operating models. **Reimagining Product Design and Customer Experience (CX)** AI-driven transformation in CX is crucial as customers increasingly expect agentic AI integration. Early adopters will be B2C sectors like retail, media, healthcare, and personal banking, where personalization sets service apart. John Mazur, CEO of Chatmeter, highlights AI’s value beyond customer interaction—using AI to analyze unstructured feedback (e. g. , reviews, social media) enables improvements in training, policies, and hiring. Generative AI also revolutionizes design thinking, prototyping, piloting, and testing by accelerating processes, enabling more testing scenarios, and integrating customer input for greater agility. For instance, in pharmaceuticals, AI enhances patient recruitment and communications during trials. Satyajith Mundakkal, CTO of Hexaware, notes that rapid generation of multiple prototypes and automated testing drastically shorten time to market. CIOs should form cross-functional leadership teams to overhaul R&D, market research, design thinking, and pilot programs. While AI improves productivity in these facets, organizations that rethink the entire design process gain the greatest benefits. **Accelerating Agile Change Management** Existing agile methodologies, product-focused IT, low-code platforms, and citizen data science have reshaped collaboration between business, data, and IT teams. Employees’ experimentation with large language models (LLMs) and agentic AI can be leveraged to hasten change management in strategic digital initiatives.

Small but substantive generative AI applications foster iterative, feedback-driven mindsets. Rob Scudiere, CTO at Verint, observes that impactful results often come from small, task-level AI deployments—such as automating micro-workflows in contact centers—yielding millions in savings, revenue gains, and improved employee and customer experiences. However, risks arise if business units lack centralized communication about AI workflows, initiatives, collaborations, and best practices. CIOs must balance independent team work with centralized information and top-down collaboration to ensure alignment with digital goals. Jon Kennedy, CTO at Quickbase, emphasizes that identifying transformative use cases requires comprehensive visibility into teams and projects to detect redundancies and gaps that hinder progress. Without collaboration, “gray work”—lost time hunting for information—impedes decision-making and outcomes. CIOs recognizing generative AI’s importance will promote agile change management and expand PMO roles to address communication weaknesses. **Reinventing the Digital Operating Model** CIOs broadly acknowledge generative AI as a major evolution in IT innovation delivery and service management. Josh Ray, CEO of Blackwire Labs, describes gen AI as an “organizational nervous system” that amplifies human intelligence, creating cognitive ecosystems where humans and AI collaborate on complex challenges, transcending mere digitization. IT service management (ITSM) offers a practical starting point; AI Operations (AIOps) platforms already aid NOCs and SREs by correlating alerts, reducing mean time to resolution, and enabling root cause analysis. With generative and agentic AI assisting more IT functions, CIOs can shift IT operations toward proactive, transformative roles. Michael Trkay, CIO at FICO, highlights AI-driven hotfix development and predictive incident management that enhance customer satisfaction, revenue retention, and engineering productivity. In software development, AI copilots are widely recognized for code assistance, with teams accepting 20–35% of AI-suggested code. Yet AI’s impact extends through the software lifecycle, including requirements gathering, test case creation, and documentation maintenance. Andrea Malagodi, CIO at SonarSource, stresses evaluating AI’s role in accelerating requirements phase using historical data and tailored prompts to reduce delivery times. Generative AI also influences organizational design, team building, and communication. Ed Frederici, CTO at Appfire, explains AI’s function as a career mentor by aligning job roles, corporate goals, and individual strengths, optimizing team composition, and streamlining communication through message summarization, email drafting, scheduling, and travel booking. CIOs focusing solely on productivity gains risk overlooking broader organizational transformations. To capitalize on AI’s rapidly evolving capabilities, CIOs must invest time understanding vendors’ agentic AI offerings, monitor employees’ AI tool usage, and continuously refine their digital operating models.