David Giambruno, VP Tivity Health, is the type of person who negotiates his exit package before ever taking a job. Why? He's going to burn your platforms, automate everything possible, cut costs and be hated by everyone at a company except for the CFO.
Sunitha Ray, Field Operations CTO at Shopify, says there's a big difference between enterprise AI and generative AI and business leaders need to know the use cases and potential returns on investment for each category.
Generative AI projects in the enterprise have moved beyond the pilot stage with many use cases going into production. Scaling has been a bit of a challenge, but the maturation of how CxOs are approaching genAI is underway.
DisrupTV caught up with the CIOs from the Boston Red Sox, Bruins, Celtics and New England Patriots. Here's a look at the takeaways and lessons learned.
CxOs aren't thrilled with their enterprise technology vendors, becoming frustrated with copilots that don't play well together, and spending a good amount of time on procurement and consolidation.
This is an ode to middle managers--the people who manage projects, serve as a buffer to executives, and lead teams in smaller batches. Today, we've gone from the COVID-19 era of over hiring to cutting out layers of management. In true American fashion, the pendulum swings all the way to the other side with little to no balance in the middle.
Enterprises are prioritizing artificial intelligence projects, but shortchanging the collaboration and orchestration needed across all business functions including HR, IT, finance, operations, and other areas. What's needed: Chief AI Officers.
Enterprise technology demand has stabilized, and vendors are expecting gradual demand improvement into the second half with pockets of generative AI-driven strength.
"We are still in the early stages of using large data models to power improved user experiences and efficiencies across our platform, with much more to come," says Uber CEO Dara Khosrowshahi.
