Latest AI Articles:

This article was originally written as part of a PDF report sponsored by expert.ai, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Increasingly, technology and business leaders look to AI project managers to make the execution (and success) of their AI projects more predictable. Executives and decision makers want AI projects to mature so they are more like the software development projects that have been with us for a generation. But, any AI project manager hoping to deliver on those expectations knows that success in AI projects requires an end-to-end thinking rarely found today.

After we’ve constructed a list of potential AI projects, and assessed their ROI and costs, we’re ready to pick the projects that we will take to leadership for approval.

At Emerj, we calculate and convey the ROI of AI across three distinct ROI categories:

Measurable ROI refers to the quantifiable aspects of AI project impact - which could include financial measures (cost savings, revenue drivers) or non-financial (reduced manufacturing equipment temperatures, improved self-reported customer service scores).

When we're building our portfolio of AI projects, one question often arises first: where can we start? We consider the respective ease of deployment offered by each AI opportunity on our list. We wonder what it will take in terms of time and money to get these projects up and running.

In the enterprise world, more and more companies are crossing the chasm to test, and then deploy, their first AI solutions. To navigate this sometimes unfamiliar territory, enterprise leaders increasingly scrutinize the AI project selection process.

Assessing the ROI of AI takes time. Not only does it require some level of research and consideration on behalf of the project leader (an internal AI champion in the enterprise, or an external AI consultant), but a project leader also often needs time and participation from various stakeholders to estimate costs, think through challenges, etc.

About AI Power: AI Power is an article series focused on the long-term consequences of AI, and how power is or will be influenced by AI technologies. Some previous AI Power articles - including "The SDGs of Strong AI" and "AI Ethics at War" have been popular over the years - but I've taken a hiatus from writing AI Power articles but suspect that I'll be creating more in 2022. I'm grateful to my friends for helping to put this first piece together - I hope you enjoy it. - Daniel Faggella

Writing content to attract B2B prospects begins with an understanding of the problems that your prospect is facing, and the solutions that your prospect is most likely to be looking for.

Enterprises are just as eager to avoid the risks of AI as they are to capture the value of AI. Over the last three years as we've seen "AI ethics" proliferate, we've seen some firms giving mere lip service to the term - and others walking on eggshells and avoiding anything AI as an inherently dangerous potential PR gaff.