Insights & Publications

A conversation on why AI adoption succeeds or fails inside real organizations, and why the technology is the easy part. Software development adopted AI fast because the work was documented, rule-bound, and built on clean handoffs. Almost nothing else looks like that, which is why returns show up only when teams go deep on a workflow and restructure it rather than handing out licenses and hoping.

The budget horror stories are coming from software engineering, but cost management is now a shared concern across every function adopting AI. Getting it right starts with defining expected outcomes before setting the budget.

Stanford's Digital Economy Lab studied 51 AI deployments that delivered measurable value. In 42% of them the foundation model was fully interchangeable, and 77% of practitioners named change management, data quality and process redesign as the hardest part.

A Forbes Technology Council expert panel on why digital transformation stalls. The throughline across contributors, including Emily: programs lose momentum when they are framed as technology rollouts disconnected from why the organization exists. Tie the change back to purpose and it holds.

New research from Anthropic, OpenAI, and Wharton reveals that the strongest AI results come from better human-AI collaboration, not more delegation, and why that reframes the entire adoption conversation.

How boards should approach AI and why shared responsibility across all directors, not just the tech expert, is the governance gap most organizations haven't closed.

Anthropic's Economic Index shows augmentation, not automation, is the dominant AI usage pattern. Here's what that means for how leaders should sequence adoption, invest in skills, and design for accountability.

As AI moves from experimentation into core operations, leadership teams must rethink ownership, shifting from a single-department model to shared decision rights across strategy, governance, adoption, and accountability.

AI infrastructure decisions are reshaping energy markets, grid capacity, and capital strategy. Here's what business leaders need to know about the build-out happening beneath the surface.

The AI "context gap," not model intelligence, is what limits enterprise productivity. Here's how leading platforms are converging on persistent workspaces, grounded retrieval, and integration as the real differentiator.

Leverage the latest in agents, stronger context, and real integration to help leaders achieve more in their own workflows and across their organizations.

A practical, non-technical walkthrough of Claude Code

Is AI adoption a choice between broad enablement or deep transformation? Evaila founder Emily Lewis-Pinnell explores why a 'dual strategy' is the only way to scale GenAI results.

Platform strategies for organizational success must prioritize context and integration, not just model performance.

Three years after the introduction of Generative AI, I reflect upon the patters learned and five basic lessons to ensure successful AI transformation.

AI is reshaping HR, but many teams stall out between interest and implementation. In this session, attendees will be guided through a practical AI adoption framework that helps them move from talk to action.

The rise of Shadow AI is a call for leaders to get serious about AI adoption.

Four Strategies for accessing AI across the Enterprise

Discussion on the impact of AI on IT and professional services firms between Emily Lewis-Pinnell and Chris Hart.

As AI reshapes the workforce, human skills in reasoning, communication, and judgement will become more important.

Companies that fail to support their workforce in these development efforts risk losing growth-minded talent to competitors who invest in skill development.

In an era defined by rapid technological advancements and the constant emergence of new tools, the need for lifelong learning and intellectual curiosity is crucial.

Transitioning to a data-driven culture is more than just a technological shift; it is a transformation in how an organization approaches problems and makes decisions.

Dive into AI treatment of biased training data, the ethicality of decisions made with AI and considerations around AI regulations.

Discussion on the challenge women tend to face when negotiating, personal experiences, and tips and best practices.

Plan for cloud cost management and other common post-migration challenges.

Smart, well scoped digital initiatives are more critical than ever when facing inflation.

Emily Lewis-Pinnell & Forrester Analyst Brett Eliis discuss research findings and real world experiences guiding cloud strategy.

The cloud advantage: speed to market, flexible scaling, and long-term efficiencies that safeguard business growth.

Culture plays a critical role in cloud adoption, meaning that leaders must plan for workforce adoption when introducing technology.