Do you agree with this prediction? Through 2023, 50% of IT leaders will struggle to move their AI projects past proof of concept to a production level of maturity.

Strategy & Architecture Data & Analytics Business Intelligence +1 more

Strongly Agree7%

Agree76%

Neither Agree nor Disagree10%

Disagree5%

Strongly Disagree0%

542 PARTICIPANTS

2.5k views1 Upvote2 Comments

Director of IT in Software, 10,001+ employees

The reason why most projects don’t leave the innovation team’s shelf is because of lack of inclusion of right stakeholders in defining objectives. It’s the case of a team that is given a hammer. To them every problem will be a nail.

VP / CIO in Healthcare and Biotech, 10,001+ employees

More strong innovative ideas required in the pipeline to enough explore and prove the technology differentiation in the production environment

Content you might like

Do you feel like security’s current role in your org’s generative AI initiatives is adequate? Or do you think the security team(s) should be more/less involved?

Artificial Intelligence & Machine Learning (AI/ML)Governance, Risk & Compliance Security Strategy & Roadmap

Way more involved5%

Somewhat more involved47%

A bit more involved30%

Security’s current role is adequate10%

A bit less involved4%

Somewhat less involved1%

Way less involved1%

206 PARTICIPANTS

1.4k views

What steps are must-haves to ensure data security in automated processes?

Security Strategy & Architecture

336 views

What are real ways enterprises will consume AI?

Artificial Intelligence & Machine Learning (AI/ML)

Partner in Finance (non-banking), 51 - 200 employees

Many AI-based applications are finally making the jump across the hype cycle from ‘promising’ to ‘delivering’ real value. Chatbots are one that have made a dent in 2017 and will continue to do so in 2018. Messaging has proved ...read more

18 2 Replies

Are you planning to send any of your developers to OpenAI’s first developer conference in San Francisco? What are you hoping to get out of it, if so?

Engineering Artificial Intelligence & Machine Learning (AI/ML)

386 views

What is the main driver for changes to your data governance strategy in the upcoming fiscal year?

Data Governance Strategy & Architecture

Business expansion12%

Changing business model45%

Compartmentalization due to localized regulatory requirements15%

Cultural changes within organization12%

Customer data privacy concerns3%

Data monetization3%

Emerging risks3%

Improving data governance maturity3%

Introducing new technology0%

Scaling data and analytics ecosystem0%

Not sure3%

We aren’t making changes0%

33 PARTICIPANTS

195 views