🎯 Enterprise AI, a toolbox for risk management
Get started with AI | How-to guides and features
I built this toolbox to be extendable in ways like you would extend.
It’s designed to be flexible and extended to fit seamlessly in any business, mind, or environment.
While working on it, I kept in mind that we have to ease the way towards our purpose.
Whether it will lie on the desk of business leaders who need to make decisions or end up in the hands of internal teams to build and support their small projects, the processes are similar — not the same — but similar.
We need solutions enabling test and learning generation and assessment collaboration to know what’s best to adopt and integrate.
This will allow the inclusion of new features and custom elements but also help us solve big questions about how we should build what we build, resilience and growth, and be part of those leading the way 1.
This is a just a reminder (links) of what we’ve been working on for the past month.
Next week, we will be sharing the agenda of the webinar series; please stay tuned.
If you have questions or recommendations, please add a comment.
We really look forward to connecting and sharing.
Again, my goal is to help you build a strong focus on understanding and integrating artificial intelligence with a positive purpose in mind—openness, responsibility, and flexibility—while choosing the right tools and applications you need to make it happen.
So here’s what to prepare for next week:
How can a better understanding of value creation be leveraged to improve the implementation of artificial intelligence from various sources in your processes?
How can the fundamental states of creating value, deploying an initiative, or even developing a new project contribute to more adoption of data-driven dynamics?
How can we use human capacities to elaborate business models to build resilience?
What is the kind of systemic processes do we need to enhance to accelerate the implementation of purpose-driven initiatives at the core of corporations?
As more companies try to adopt AI in one way or another, business leaders grapple with virtuous decisions about its design and use.
Global AI regulations will eventually address challenging concerns, but they won't be uniform and won't provide the needed solutions.
So, until then, we will need to work to bridge the gaps. And there are many.
Over the upcoming weeks in the “How-to” section, we will discuss best practices for instilling integrity through governance across the AI lifecycle.
A 5 part series extracted from a workshop “Enterprise AI, a toolbox for risk management”2, to help you understand:
An improper implementation, a socially insensitive data label, or negligent data management can easily lead to an auditing nightmare:
How can you adapt to new AI technologies with ease?
What are the best practices to safely utilize and govern AI?
How can you ensure that your AI project does not become a liability?
This is an extract from the upcoming workshop: “Enterprise AI, a toolbox for risk management,” which will take place over Q1 2024. As a premium member, you will receive an invitation to participate.