Digital Transformation Leadership

Uncover the 11 major barriers to AI adoption and learn effective strategies to overcome them, enhancing efficiency and innovation in your organization.

Find out what a chief artificial intelligence officer does and whether you need to add one to the C-suite to drive AI and generative AI value.

Billions of dollars will be wasted on AI over the next decade. If that sounds like a contrary take, it shouldn’t.

Businesses that prioritize generative AI use cases can maximize their value capture, speed, and efficiency.

The integration of AI into every aspect of business operations isn't a distant future. It's happening now.

In 2024, enterprise leaders are doubling down on their genAI investments. 16 developments for founders to keep in mind to capture this new opportunity.

CTOs play a strategic role in helping organizations protect corporate data as they implement generative AI tools in the workplace.

A lot of different skills are needed to create a system that can do the most for your business. Here’s a description of the important roles.

Don’t buy your next ERP, CRM, HRMS, etc. solution quite so fast. You might want to seriously investigate what each vendor is doing (or not) vis-à-vis its new AI-fueled applications/solutions.

The technology is a marvel, but leaders are ready to see results. Here are three value plays organizations should make now.

It’s understandable for business leaders to be experiencing AI anxiety, particularly in the current climate.

There are three drivers of AI scale: community, commonality, and coordination. Companies should enable their explorers, build platforms instead of buying products, and prioritize for impact.

Companies are looking for safe and cost effective ways to leverage the capabilities of generative AI and large language models. In this recap from our recent webinar, we discuss the adoption strategies that deliver value.

Leaders have to consider many variables with AI adoption, which can lead to pitfalls. Here are five to avoid.

Enterprise organizations are not merely seeking point solutions; they are pursuing a comprehensive architectural overhaul that places AI at the core of their strategies.

Achieving competitive differentiation with AI — and staying ahead of commoditization — requires accompanying business transformation.

Generative AI can bring a host of ideas—and a critical “outside the box” perspective—to teams working through the innovation cycle.

Commonly, many AI projects fail for the same reason digital transformation projects fail.

The problem with an AI-first strategy lies not within the “AI” but with the notion that it should come “first” aspect. An AI-first approach can be myopic, potentially leading us to overlook the true purpose of technology: to serve and enhance human endeavors. Instead, the author recommends following 3Ps during an AI transformation: problem-centric, people-first, and principle-driven.

AI could very well be the turbo boost your business needs.

Despite the current level of hype and mainstream adoption, gen AI still needs to experience the trough of disillusionment before embarking on a path to peak productivity.

Companies across industries rushed to adopt ChatGPT last year, seeing its potential to streamline tasks formerly handled by people and vendors at much higher cost. As generative AI enters its next phase in 2024, what can leaders expect? Harvard Business School faculty members highlight four trends to watch.

Artificial intelligence will impact most business activity in the economy. Some functions will be less impacted but even the lightly-affected companies will change.

There’s a lot of talk but not many actual implementations of generative AI in the cloud. Better to have all the pieces in place before launching expensive projects.

KubeCon + CloudNativeCon just concluded with another land grab for generative AI. What does this mean for the enterprise?