The Real Cost of AI: An InformationWeek Special Report

It’s really getting a bit out of hand, isn’t it? Governments are vying for AI dominance with a desperation reminiscent of the nuclear arms race. The market is as moody as a teenager — a rabid fan of AI one second, and totally over it the next. Major enterprises cut staff and elected officials bend land use rules all as part of exciting “strategic AI investments.”

American AI companies have invested hundreds of billions to build AI tools, while a Chinese AI startup claims to have whipped one up in a few million. While some media companies are meeting AI giants with multimillion-dollar lawsuits, others are meeting them with multimillion-dollar partnerships. The Screen Actors Guild is fighting to prevent studios from making AI-generated versions of movie stars while movie stars are starring in ads for AI companies during Monday Night Football. AI can solve the knottiest challenges of the climate crisis, some say, but running AI may worsen the climate crisis. There are oodles of new AI-enabled cybersecurity tools on the market, which you will need, to defend against new AI-enabled cyberattacks.

And despite this, despite all the bells and whistles, sturm und drang, many CIOs look at their own AI story and find it … a little boring.

A bit slow and tedious, maybe. The same basic story line: behind schedule, over budget. Even if they see a positive return on their investment, the project might be a letdown.

So, what is the real cost of AI? What’s the price tag CIOs have to pay in the short term and what’s the cost to their business — and to society — in the long-term?

That’s a long question. So in this special report that we’ll roll out across three weeks, InformationWeek will delve into direct and ancillary costs of investing in AI. What are the various costs of developing AI internally versus hiring third-party resources, the impact on community, the environment through the drain on power, and regulatory enforcement on the technology. What will it cost an enterprise in real and social currency to pursue AI? And can we afford what it will take to deliver on AI’s promise?

Week 1: The costs and the hidden costs.

Video: What Is the Cost of AI: Examining the Cost of AI-Enabled Apps

The path to realizing those AI expectations, however, comes with a variety of costs that are not all monetary — and could have surprising impacts on the world.

Video: If Everyone Uses AI, How Can Organizations Differentiate?

As AI saturates the market, what becomes of its competitive advantages? Does it become a basic, digital commodity in the background?

Here’s what’s coming next:

  • AI’s Hidden Cost: Will Data Preparation Break Your Budget?

  • Infographic: Comparing Costs of LLM Providers

  • Optimizing AI: What Do Companies Need to Focus On?

  • It Takes a Village: New Infrastructure Costs for AI — Utility Bills

  • Dissecting The Darker Side of AI

  • What Types of Liabilities Are Emerging From AI? 

  • Who’s Hurting from the AI Talent Shortage

Week 2: The sudden demands for AI, particularly generative AI, have outpaced the world’s ability to supply it.

  • How Bad is the AI Chip Shortage Now, and How Does That Impact the Price of Your AI Project

  • The Long-Term Impact of the AI Market Crash of Summer 2024

  • Cooling AI: How Hard Is It To Keep Temps Down

  • Why the Grid Can’t Support AI

  • MAP: How Hot are AI Hotspots?

  • Spotlight: Loudoun County, Va.

  • Spotlight: Phoenix, Arizona

  • Spotlight: Santa Clara County, California

  • Just How Rare are the Rare Earth Metals We Need for AI?

  • How Will Politics Limit or Complicate US Access to AI?

Week 3: How can you use AI more efficiently and more effectively, to keep costs down and improve outcomes?

  • Is a Small Language Model Better Than a LLM for You?

  • How to Determine ROI for an AI Project.

  • How to Make Your AI Project Greener, Without the Greenwashing

  • How to Set a Realistic Budget for AI

  • Research Projects Working on Truly Green AI


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