Contrary to popular belief, risk management doesn’t mean slowing down and saying “no” to everything.
It means learning how to place smarter bets and steering clear of pitfalls so you can improve your chances of winning. It can reduce your exposure to problems while leaving you open to the potential upside. You’ll move faster and experience fewer upsets along the way.
AI risk management can improve your project planning, product management, hiring, vendor evaluation, and due diligence procedures. All while limiting your exposure to project failures, reputation problems, and ethics issues. That makes your company more attractive to prospective customers and potential hires. And also to investors.
AI risk management: your guiding light
If AI is a dark road, then AI risk management lights the way for:
Company leadership: Vendor pitch materials and press success stories vastly oversimplify AI and paint too rosy of a picture. Understand what AI can (and cannot) really do and see how to put your company’s data to good use. Establish controls and policies to prevent costly PR mishaps.
Product management: AI requires a shift in how you design and implement products. Create AI products and embed AI into products, in a way that will avoid embarrassing and expensive problems down the road.
Project execution: Compared to traditional software projects, AI projects exhibit a special set of pitfalls and failure modes. Learn to steer clear of those problems so you can make the most of your effort and reduce your time-to-market.
Investors: Sadly, there’s no shortage of fraud in the startup scene. The hype around AI gives startups an extra smokescreen to cover bad practices. Get extra eyes for your due diligence efforts before investing in or acquiring that startup.
Who’s behind this?
I’m long-time AI consultant, researcher, and published author Q McCallum.
I’ve been in this field since the terms “predictive analytics” and “Big Data” were still getting traction. I’ve written books and papers on the intersection of AI and business. I’ve discussed AI strategy with the C-suite, developed and deployed AI models at the tactical level, and worked closely with product teams on embedding AI in their company’s offerings. I have taken companies from zero to AI.
I’ve also seen what happens when AI goes wrong. From the companies that were leaving their entire AI operation to chance, to the job postings that sat unfilled month after month, to the companies that threw away money while chasing an ill-defined AI dream.
And I say that risk management is the solution to this field’s biggest problems.
Don’t believe me? Ask successful traders, lenders, and insurers how they ultimately make their money. They’ll tell you that risk management is a key ingredient. It’s how they place smart bets and hedge against potential problems.
It’s time we brought that same mindset to AI.
How do we begin?
Do you want experienced AI guidance to help you see around corners and place smarter bets?
Are you ready to position yourself to win more often with AI?
Then we should talk.
You can browse the list of services, or reach out to get started.
Risk Management for AI 