Digital Transformation Leadership

Artificial Intelligence is not a strategy, a tool, or a trend. It’s a threshold.

Too many companies are rushing to embrace the latest agentic AI innovations without considering the part played by best practice and governance structures.

With AI and, in particular, agentic AI now in the mix, the conversation on where to deploy your AI isn’t cut and dried.

AI at scale succeeds when teams are ready first. Build curiosity, clarify roles and redesign workflows before expanding technology.

The flood of organizational requests for AI requires a strategic and structured approach driven by dedicated teams tightly aligned with business requirements.

Why AI is turning cloud spend into a board-level concern, and why CFOs must now own the economics behind every compute decision.

R&D has been getting more difficult and more expensive. We look at how AI can accelerate the process and usher in a new era of growth across industries.

By studying 100 brand implementations of gen AI, researchers have discovered four archetypes for how companies are using the technology strategically. Bold innovators seek to reshape their markets with gen AI. Disciplined integratorsfocus on trust, control, and compliance. Fast followers target quick wins, using gen AI for low-cost, high-impact solutions.  Strategic builders take a long-term view, developing gen AI to own IP and drive sustained advantage.

It’s an artificial intelligence hype cycle Robert Blumofe sees far too often: Business leaders hear an anecdote about an early-stage AI breakthrough, mistake it for a mature use case, fear that they’re missing out, plunge headlong into adoption — and end up with an implementation that falls short of expectations.

The answer to 'What customer needs requires an AI solution?' isn’t always 'Yes.' LLMs are still expensive and not always accurate.

GenAI platforms can help organizations acclimate to an environment of higher-frequency change and adaptation.

Agentic AI and digital twins are reshaping enterprise architecture, enabling dynamic, autonomous governance through real-time simulations.

Why AI may be accelerating bureaucracy, not breaking it, and why true transformation depends on rethinking systems, not just adding new tools.

95% of Enterprise AI Stuck in Pilot Purgatory: How Do the Rest Succeed?

The question isn't whether to invest in AI, but how to ensure those investments translate into measurable, real-world payoff.

AI is already spurring CIOs to rethink how they run IT departments, invest in technology platforms, and digitally transform businesses. But a clear-eyed view of IT’s future remains elusive.

Leaders are repeating the mistakes of the digital transformation era by funding scattered pilots that don’t connect to real business value. The takeaway is not that AI experimentation is broken, but that it must be disciplined

Ultimately, model makers and enterprises are focusing on the wrong issue: They should be computing smarter, not harder.

The competition to turn artificial intelligence (AI) into business value is heating up, but business leaders need the right tools to make AI deliver

Accenture's new research reveals the critical strategies that separate the companies successfully scaling AI from the 92% stuck in perpetual pilot mode, providing enterprise leaders with actionable insights to accelerate their AI transformation journey.

AI is everywhere, but it can be difficult to cut through the hype to understand how to leverage the latest innovations to gain a real, measurable competitive advantage.

Despite cost cuts and paused capital spend, finance leaders are prioritizing targeted AI investments for competitive advantage in H2 2025.

The modern CFO must balance immediate priorities while keeping a laser focus on how AI is influencing strategic innovation, C-suite relationships, and helping tackle regulation.

As companies deploy agentic AI, CIOs and data leaders face a critical mandate: deliver governed, trusted data that AI systems can understand.

Companies that rushed to replace human labor with AI are now shelling out to have IRL workers to fix the technology's screwups.