Apply my AI experience principles to your business. 90 minutes live interactive workshop exclusively for your business plus additional Q&A. Artificial Intelligence myths, opportunities, principles and strategic approaches. Satisfaction guarantee pay only on completion.
- 3 P's of implementation
- GPT4 and others explained
- What it matters to you
- Embracing the opportunity
- Evaluation and strategic road map
Recording, transcript, exec summ, materials, your questions answered guarantee.
AI is all the rage today; business leaders feel pressured to develop AI capabilities, but it's not clear how to get started. Ed Wiley is here to help. A Stanford PHD, high-visibility senior executive with more than 20 years of building, leading, and advising world-class AI teams at US Government and companies at stages from startup to Fortune 50.
Bringing AI to business is not like your typical IT implementation; building an AI practice requires consideration across functional areas and carries substantially risk of failure due to factors very different from those managed in an IT implementation. Ed has been there before, and solved tricky issues across contexts, functions and sectors.
Background to Ed.
Few careers in AI have been as long and as varied as Ed's. Ed brings decades of experience to his work as an advisor; he has worked with AI as a doctoral researcher, as a McKinsey consultant, as a Fortune 50 executive, as a professor and doctoral program Chair, as a partner with the DEA and other federal agencies, and as a founder and executive in multiple startups. He knows what is critical to consider in building an AI practice or executing an AI project, and can also help guard against missteps and pitfalls that can doom your practice or project. After working with AI across such varied contexts, Ed knows what to do - and what NOT to do - when working with AI.
Ed Wiley is your AI sherpa. He's made multiple climbs on the AI mountain. He's successfully summitted AI peaks, but also bears the scars of efforts that failed. Those failures hold great value -- I've seen projects doomed by mistakes that stem from seemingly reasonable decisions, so I'm well equipped to help clients take steps to avoid those risks and set themselves up for success.
An AI strategy must be driven by overarching business strategy and operations. As such, before addressing the '3 P's', a critical starting point for any strategy development is articulation of a business’ strategic objectives and identification of opportunities for data science-based transformation in targeting those objectives.
Ed's '3 P's of AI Implementation'
The human capital component of data science is critical to delivering on a successful strategy. Who do we recruit, hire, and train for our AI function? How is the AI function structured in order to deliver value to our business? Building the AI team takes more than simply opening up a bunch of job recs for AI engineers.
A high-functioning AI practice follows specific processes to carry out the early 'research-y' stages of an AI project; when the project is ready for adoption, attention turns to how best to structure efforts to integrate an AI model into a company's digital ecosystem. How can we have our AI engineers and data scientists approach their work in a structured manner? How can we leverage data, AI, and data science to foster a data-driven culture throughout the business?
Finally, executing your AI strategy requires technology—technology for data and technology for machine learning. Technology needs are unique to each business; they depend on the types of data to be leveraged for AI, the form and magnitude of that data, the types of AI models that a business plans to create, and the overall scale of operations represented by those AI models. Many parameters must be considered both in creating a data and data architecture strategy, and in building a machine learning architecture to support AI initiatives.