2026 enterprise AI predictions — fragmentation, commodification and the agent push facing CIOs

Three years post-ChatGPT, enterprises are increasingly prioritizing agentic systems built on large language models (LLMs). Predictions for the coming year include heightened competition among automation approaches, a shift towards strategic investment in agentic solutions, and necessities surrounding data quality and compliance. Challenges, such as rogue agents and unstructured data, persist.

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Why Leaders Need to Take Play Seriously

Play is essential for creativity, resilience, and innovation, not just a childhood pastime. As adults, we often neglect play, which can lead to burnout and stress. Rediscovering play enhances well-being and fosters deeper connections among leaders, encouraging a culture of curiosity and creativity in workplaces. Thus, play is vital for survival and fulfillment.

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What will IT transformation look like in 2026, and how do you know if you’re on the right track?

As enterprises focus on digital transformation, IT departments must evolve culturally, operationally, technologically, and structurally by 2026. Current challenges include fragmented data and legacy systems. Successful transformation requires better alignment with business goals, measuring performance in terms of business value, and fostering strong partnerships across departments.

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Rethinking Organisational Well-Being

Companies, including Google and Meta, are scaling back investments in employee wellness programs, reflecting a shift towards cost savings. While this may seem practical, it undermines individual well-being and organizational performance. A successful future demands integrating well-being as a fundamental principle, measured alongside productivity, and reshaping toxic workplace cultures.

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Vendasta Shows Why Platforms Become Operating Systems For AI Agents

Vendasta has transformed from a basic reputation management platform into a comprehensive operating system for AI agents, enhancing client engagement and automating core functions for small and medium-sized businesses (SMBs). This pivot allows partners to onboard clients swiftly and deliver customized experiences, unlocking significant growth potential and improving efficiency.

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Skeptical Intelligence: Disciplined Doubt for AI-Powered Innovation

Artificial Intelligence (AI) is viewed as a key transformational tool in organizations, yet the ability to critically question AI-generated insights, termed Skeptical Intelligence (SI), is becoming increasingly essential. SI, which focuses on disciplined inquiry and validation of claims, complements IQ and Emotional Intelligence (EQ), enabling leaders to navigate a complex decision-making landscape effectively.

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Build Or Buy AI Agents: Why This Choice Matters More Than You Think

Organizations are rapidly transitioning from debating the use of AI agents to determining their deployment strategies. The key decision lies in choosing between off-the-shelf solutions or custom-built agents, each with distinct advantages and drawbacks. This choice impacts costs, compliance, data control, and competitive differentiation, necessitating careful consideration of organizational needs and capabilities.

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How a CIO can break bad news without killing team morale

CIOs must navigate challenges like layoffs, project failures, and staff relocations by communicating transparently and maintaining trust with their teams. Leaders should address changes clearly, focus on individual support, and encourage problem-solving to enhance morale. Honesty and timely communication can help teams cope with adversity effectively.

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The Download: why 2025 has been the year of AI hype correction, and fighting GPS jamming

The Download highlights significant developments in technology, including the AI hype correction of 2025, as expectations clash with reality after ChatGPT’s impact. Quantum navigation offers promising solutions to GPS jamming concerns. Other topics include government tech initiatives, AI’s transformative role, and China’s youth embracing AI fortune-telling amid societal anxiety.

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Accenture, Anthropic and the quiet rise of AI integrators

Accenture and Anthropic’s expanded partnership highlights a shift in enterprise AI strategy, focusing on upskilling 30,000 Accenture employees in AI technology. As organizations face talent shortages and complex AI ecosystems, integrators play a crucial role in overcoming challenges, ensuring effective AI implementation, and fostering internal capabilities while managing dependencies.

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How one controversial startup hopes to cool the planet

Stardust Solutions aims to combat climate change through solar geoengineering by developing technology to disperse reflective particles in the stratosphere. With $60 million in funding, the Israeli startup plans to provide nations with solutions to cool the planet. However, skepticism exists regarding its feasibility, governance, and public acceptance of geoengineering.

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How to Orchestrate Your Own Business Ecosystem

Digital platforms like Klarna evolve from supporting roles to ecosystem orchestrators, enhancing customer journeys and creating diversified offerings. Successful orchestration requires deep customer understanding, a critical mass for network effects, and substantial investment. Examples like Klarna, Kaspi Bank, and Discovery illustrate strategies for scaling from simple offerings to comprehensive ecosystem leaders.

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The great AI hype correction of 2025

The release of ChatGPT in late 2022 sparked optimism and rapid advancements in AI technology, but by 2025, disillusionment is evident. AI companies struggled to meet inflated expectations, with many projects failing to scale. Despite setbacks, continued research indicates potential for future developments, necessitating a reevaluation of AI’s role and capabilities.

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Welcome To Jr. High, GenAI

Generative AI for language is evolving, with enterprises facing challenges in governance, trust, and ROI. Despite widespread use, only a small fraction report positive impacts on earnings. Six emerging use case categories reflect the current landscape. Companies must align AI deployments with financial goals, invest in data infrastructure, and empower talent to navigate these changes.

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