I wasn’t planning for a post during this holiday week.

You’re all very busy, and I know how hard it is to keep up with your reading, leading, and personal development. So, before we say goodbye to 2024, I thought I would pick out some of the key articles and topics I covered this year.

Top Articles of 2024

Almost half of my articles in 2024 covered AI, but I didn’t leave behind articles on leadership, transformation, devsecops, agile, data, and other topics on innovation. I published 92 articles in 2024, my lowest total since 2018. But there are several articles that you shouldn’t miss.  

Want more? Please visit Search to see a dashboard of all my articles and search for ones on Drive. You can also sign up for the Driving Digital Newsletter to get an update on all my latest thought leadership.

Happy New Year!

My top posts on Drive

1. 20 expert gen AI predictions for an ambitious 2025
2. How to energize your IT career as an innovative digital trailblazer
3. What gen AI should tech innovation teams review in 2025
4. 5 smart ways CIOs can hedge their 2025 transformation investment plan
5. Change management: 10+ ways to ease adoption in digial transformation

Posts on Drive that should have received more attention

1. Why innovation labs fail and 5 ways to deliver meaningful results
2. Why SaaS and low-code need AI for helpful technical support
3. Why Digital Trailblazers must be paranoid in the four important areas
4. 10 interview questions for digital trailblazers: find amazing candidates and land exciting jobs
5. It’s not skill gaps holding back digital transformation and innovation

Must-reads from my articles on CIO.com

1. 10 ways to kill your IT culture
2. Rebranding IT for the modernized IT mission
3. Digital KPIs: The secret to measuring transformational success
4. 5 IT risks CIOs should be paranoid about
5. 5 tips for better business value from gen AI

Top topics from my articles on InfoWorld

1. AI/ML articles on what you need to know about AI governance, how agentic AI impacts the future of work, seven reasons ML misses business objectives, and how data scientists can prepare for gen AI transformations.
2. Data technologies I covered include why your organization may need a data fabric, choosing a data analytics platform, and the definitive guide to data pipelines.
3. DevOps articles include 12 principles for improving devsecops, four devsecops skills for the gen AI era, advanced CI/CD, and avoiding deployment horrors.
4. Low/No-Code and automation articles include agile/devops for these platforms, innovative ways to use these platforms, choosing a low/no-code platform, and how gen AI changes low-code development.
5. Leadership articles you should read include transforming the architecture review board, the role of data science product managers, and developing business acumen.