Does it make sense for you to use ChatGPT at Work? OpenAI's ChatGPT stormed onto the global stage last year, instantly redefining expectations for personalization and efficiency across industries and getting the attention of the boards and C-Suites across industries. But...is it the right solution for most companies? This post highlights the tradeoffs leaders should consider when delving into the world of generative AI.

There is a growing interest in Generative AI among organizations, but there are a few key hurdles slowing down it’s adoption. Issues like data privacy, 'black box' concerns, costs, potential bias, and contextual challenges persist. There are practical solutions to each of these concerns so companies can move forward confidently and leverage the transformative power of Generative AI.

Episode 3 of the ‘AI Impact’ series focuses on how AI works, including the capabilities driving new possibilities and an overview of the 3 forms of machine learning.

Harness the power of the 'Flywheel Effect' in innovation and AI practice: Identify your business's key drivers, make data-driven incremental improvements, create a virtuous cycle of success, and measure your progress with real-time dashboards. Like riding a Peloton bike, every effort contributes to momentum, making the next action easier. Set your innovation flywheel in motion and experience sustainable growth!

Venturing out on an innovation journey without a roadmap is risky, inefficient, and fraught with potential pitfalls. But, by using OKRs, businesses can align their teams with a bold vision and achieve transformative (and measurable) outcomes. Pioneered by Intel and adopted by tech giants like Google, Amazon, and Microsoft, OKRs provide a simple yet robust framework to innovate with confidence.

Whether it’s building an AI portfolio or driving a data monetization strategy, the OKR framework ensures you're not only keeping up with the pace of technological evolution but are also leading the charge.

Episode 2 of the ‘AI Impact’ series provides an overview of the history of Artificial Intelligence and the forces enabling breakthrough performance.

Episode 1 of the ‘AI Impact’ series highlights what Artificial Intelligence is and how it can be applied to solve business problems.

After reading several books from Ryan Holiday on stoicism, I started to draw connections on how organizations can incorporate wisdom, courage, justice, and temperance as they build data & AI strategies that will stand the test of time. By leaning on these principles, you can create economic value while building a better, fairer, and more enlightened digital world.

Is it possible the greatest risk to organizations from AI isn't robot uprisings but our over-simplification and underestimation of AI's capabilities and intricacies? Leaders often see AI as a simple, static field, failing to acknowledge its complexities. To navigate responsibly, we need a mindset of continuous learning and discovery, embracing the complexity of AI and fostering open conversations to harness its full benefits and mitigate risks.

Generative AI is poised to radically reshape workplaces, transforming management & hierarchical structures into agile, decentralized organizations. Beyond automating routine tasks, AI will revolutionize team dynamics, foster global ideation, and spur new roles like AI Ethics Officers. Over the next decade, organizations will gradually integrate ai, requiring a cultural shift towards continuous learning and adaptation.

In today's data-driven business landscape, extracting maximum value from your data strategy is no longer a luxury; it's a necessity. But, a "command and control" approach where a heroic leader directs data scientists to conquer use cases often fails. Instead, leaders should take a "gardening" approach - creating the right environment for growth and empowering teams to thrive.

Screenwriters seek AI usage restrictions, fearing job losses and loss of creative control. Have we reached the point of no return where the creative fuel for AI is already embedded in ChatGPT and related models?

Learn about Steve Blank’s approach to learning directly from customers for your next product innovation.

Why are companies hesitant to embrace AI? Are you forging your own path or just following the herd? There are plenty of reasons to be slow to act with full-scale AI adoption, but the innovation laggards may find themselves disrupted soon.

The post here summarizes how I used Firefly to reimagine the Mona Lisa, getting a little help from ChatGPT along the way. Needless to say, the results turned out 10x better than even the best student of Bob Ross could dream up.

Kurt Vonnegut knew a thing or two about being open to new ideas and perspectives. Now more than ever, it's critical to expand the frontiers we chase in business by exploring the edges of technological possibility so that we can reinvent experiences for users before our competitors do.

As businesses collect more and more data, they are looking for ways to turn the expense of storing raw data into valuable insights and new revenue streams.

Most leaders know that it's far more costly to hire a new employee than retain an existing one, but what's leading good employees to quit?

It's not about how pixel-perfect design or top-notch engineering, but about mindset -- a humble yet hungry desire to solve a problem while being open on how you get there.

Controversy ignites as AI-generated art is displayed in a prestigious museum exhibition, sparking debates about the role of AI in the art world. The clash between traditionalists and supporters of AI extends beyond art, raising questions about its potential impact on other fields like engineering and marketing.