Remove Experimentation Remove Measurement Remove ROI
article thumbnail

10 AI strategy questions every CIO must answer

CIO Business Intelligence

How does our AI strategy support our business objectives, and how do we measure its value? Meanwhile, he says establishing how the organization will measure the value of its AI strategy ensures that it is poised to deliver impactful outcomes because, to create such measures, teams must name desired outcomes and the value they hope to get.

Strategy 141
article thumbnail

Enterprises willing to spend up to $250 million on gen AI, but ROI remains elusive

CIO Business Intelligence

Leaders are putting real dollars behind agents, but with mounting pressure to demonstrate ROI, getting the value story right is critical. High expectations, but ROI challenges persist Despite significant investments, only 31% of organizations expect to measure generative AIs return on investment in the next six months.

ROI 81
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

How to Set AI Goals

O'Reilly on Data

Customer stakeholders are the people and companies that advertise on the platform, and are most concerned with ROI on their ad spend. Technical sophistication: Sophistication measures a team’s ability to use advanced tools and techniques (e.g., automated retirement portfolio rebalancing and maximized ROI).

article thumbnail

Escaping POC Purgatory: Evaluation-Driven Development for AI Systems

O'Reilly on Data

ML apps needed to be developed through cycles of experimentation (as were no longer able to reason about how theyll behave based on software specs). The skillset and the background of people building the applications were realigned: People who were at home with data and experimentation got involved! How will you measure success?

Testing 168
article thumbnail

What you need to know about product management for AI

O'Reilly on Data

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture. Measurement, tracking, and logging is less of a priority in enterprise software.

article thumbnail

Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

A properly set framework will ensure quality, timeliness, scalability, consistency, and industrialization in measuring and driving the return on investment. It is also important to have a strong test and learn culture to encourage rapid experimentation. What do you recommend to organizations to harness this but also show a solid ROI?

Insurance 250
article thumbnail

Learning from the AI leaders

CIO Business Intelligence

Research from IDC predicts that we will move from the experimentation phase, the GenAI scramble that we saw in 2023 and 2024, and mature into the adoption phase in 2025/26 before moving into AI-fuelled businesses in 2027 and beyond. These ROI expectations exist despite many surveyed organisations not having a clear AI strategy.

ROI 59