Why 2026 Will be the Year of Data Integrity

Written By Sydney Lauro

Deloitte’s recent technology, media, and telecom predictions for 2026 hit on an important truth: AI hype will quiet down as organizations shift from chasing the headlines to doing the unglamourous, high-impact work of making AI usable at scale. 

And while Deloitte is right that the gap between promise and reality is narrowing, there’s a catch. The biggest barrier to AI transformation isn’t the next algorithm or model. It’s the foundation beneath it all—your data and the infrastructure powering it. 

The AI Nirvana Reality Check 

Everyone wants the “nirvana” of AI-driven insights and automation. Of course we want predictive analytics, more workflow automation, and lightning speed decision-making.  

But the CEOs I talk to are starting to roll their eyes at all the talk. They know you can’t train AI on chaos. 

Fragmented, inconsistent, siloed data kills the dream. 

You can’t scale artificial intelligence on shaky ground. And you certainly can’t trust it. 

That’s why we think the most important work in 2026 won’t be glamorous. It will be all about normalizing, governing, and unifying data, so AI models have that solid foundation to learn from. 

This is where Carma steps in, by helping companies create a data model that’s actually AI-ready. 

The Hidden Cost: Infrastructure Under Pressure 

While Deloitte’s trends focus a lot on where AI is heading and the potential challenges. I have to call out that AI scaling is requiring an infrastructure revolution. 

The demands of AI are having a huge impact on our network and digital infrastructure. 

  • Compute demand is skyrocketing in data centers, putting pressure on providers to innovate power and cooling technology. Not to mention, to keep track of every single kilowatt to maximize efficiency. Kilowatt-level billing and energy optimization aren’t optional anymore. 

  • Network providers are then under pressure to deliver bandwidth to support this immense surge in AI 

  • And to top it all off, the talent landscape is shifting. Data engineers, infrastructure architects, and sustainability specialists will be in high demand. In a tightening labor market, the fight for top talent will remain fierce. 

Why Data Integrity Has to Be Priority One 

In 2026, the companies that come out on top won’t be the ones chasing the carrot. They’ll be the ones who: 

  • Invest in data integrity as a top priority 

  • Investigate their data across systems to uncover the hidden gaps 

  • Build cross-functional teams that understand the big picture 

AI Isn’t Magic—It’s Methodical 

Deloitte predicts progress will come less from headline-grabbing models and more from fundamentals. We agree. 

2026 will be the year companies stop chasing AI headlines and start building the foundation for real intelligence. That means: 

  • Data normalization becomes a board-level priority. 

  • Infrastructure modernization accelerates, from power management to network resiliency. 

At Carma, we’re already seeing companies recognize this shift. We’re helping providers normalize their data, find the gaps, and then fill them. 

When your data is clean, unified, and accessible, AI stops being a buzzword and starts being a business driver.

Author Bio: Phil Hettinger 

Phil is Carma’s CRO and a telecommunications industry leader with extensive experience driving growth for firms. He has held key sales roles at March Networks, Cyan, BTI Systems, and Ciena, helping to launch new products, expand global markets, and build customer relationships. At Carma, Phil focuses on enabling our customers to solve critical industry challenges with our best-in-class software. 

Sydney Lauro