Each New Year brings new excitement in the data analytics industry. However, this year is shaping up to be transformational for many organizations across the Data & AI landscape.

As we wish each other a Happy New Year - I have a hunch this year will be filled with Data & AI adventure, sweeping transformation, and dare I say, some unpredictability.

At Fulton Analytics, we have a front-row seat to our client’s data transformation journey’s. Our Data Success Framework help guide us along the way. In this article, I want share a vision for the future and outline 25 Data & AI Trends to Watch This Year.

1. Industrial Revolution 2.0

Many believe we are at the dawn of an AI Revolution, one which will rival that of the great industrial revolution. Data & AI innovation is set to reshape commerce, transform the digital economy, and disrupt traditional systems that have remained largely unchanged for the last 75 years.

A recent Goldman Sachs report predicts that Artificial Intelligence could replace 300 million jobs by 2030.

Experts believe the AI revolution’s potential lies in its ability to amplify human capabilities and redefine industries and social systems, just as the Industrial Revolution redefined economies and society as a whole.

2. Shift from AI Curiosity to Inception

Last year was fueled by AI curiosity - as we all explored how to incorporate artificial intelligence into our jobs and our daily lives.

Heading into 2025, organizations are formalizing their roadmaps to justify the ROI behind their artificial intelligence ambitions. Many of the organizations we are advising are planning an Inception Phase this year to prove out these capabilities.

3. A Fabric Built for Data & AI

Organizations can no longer ignore building a unified ecosystem for their Data & AI capabilities to become fully integrated. Technology leaders like Microsoft have already begun streamlining their products into a modern data fabric ecosystem to accelerate data driven innovation.

4. Renewed Focus on Data Semantics

This year companies will place a renewed focus on centralization, standardization, and automation. Ignoring the semantics will be disastrous. Well-orchestrated data preparation will be more important than ever. In the Microsoft Fabric ecosystem, Semantic Models have become the cornerstone of Data & AI innovation.

5. AI Innovation Will Be Costly

AI innovation will be exciting - but for many organizations it will also be very expensive. Massive models coupled with compute power will rack up large bills. Companies will have to rethink how the calculate ROI for each of these investments.

6. Dashboards Live On

Spoiler alert. Natural language capabilities will not kill reports and dashboards. Yes, it’ll reshape how executives interact with their data. Dynamic reports will live to see another day. Platforms like Power BI will survive and serve a purpose, much like Excel spreadsheets and paginated reports have before them.

7. Excel the “Comeback Kid”

As much as it pains me to say this - Excel is poised to become even more powerful through a bevy of AI integrations. Calling Excel an AI tool sounds crazy, right?! But tools such as Microsoft CoPilot and ChatGPT will only enhance Excel and allow users to do more within their favorite data platform.

8. AI Powered Automation

Conversations around AI have also fueled interest around RPA and Intelligent Automation, with many companies exploring tools like Microsoft Power Platform. For a number of companies, driving efficiency through automation is more tangible than widespread AI adoption.

9. Data Science Reincarnated

Countless organizations lost millions of dollars, and data scientists lost their jobs over failed data science initiatives. Expect to see data science reincarnated and rebranded as Predictive AI - with a laser focused on aligning to tangible business value and outcomes.

10. AI “Gold Rush” Movement

Just like the Gold Rush - AI innovation has already spurred a boom of economic opportunity and wealth creation for the pioneers across the AI landscape.

It’s still early, and many organizations are still crafting a strategy to navigate this rapidly changing landscape. Even so, many of these efforts will fail as the industry evolves. Once this is clear though, it will indeed create an economy for those who provide the requisite tools and infrastructure to support the AI revolution.

Those navigating this adventure will benefit from having stable technology teams, openness to innovation, realistic aspirations, and trusted Data & AI partners.

11. Integration of AI Agents

Every software application we are using today, whether it’s LinkedIn or Squarespace (where I’m writing this blog), has an “AI button” for enhanced functionality. Many organizations will find it more cost-effective to leverage these pre-built agents versus trying to build their own LLM and AI solutions from the ground up.

12. Surge in Industry Focused Prescriptive AI

Where data science initiatives and predictive analytics projects missed the mark - is that they failed to produce actionable intelligence that was directly tied to business impact. This time around, organizations will ensure these investments impact the bottom line.

13. Cloud AI Services

This year will be like a kid in a candystore experience. The number of pre-built Cloud AI services is staggering across platforms like Databricks, AWS, Google, and Microsoft Fabric. It’s an arms race to both capture marketshare - and streamline user adoption. 18-months ago it was just ChatGPT. Now there is an entire ecosystem of AI services like Google’s Gemini, Microsoft’s CoPilot, X’s Grok, and others.

14. AI for Cybersecurity

As this threat becomes more sophisticated - we will see artificial intelligence be used to combat cyber-attacks and help prevent these attacks.

15. AI Integration with Digital Currencies

By now most people have heard of Bitcoin - but maybe haven’t stopped to fathom how AI innovation will intersect with Digital Currencies (crypto currency). In the age of AI, the technology will need the ability to transact instantaneously, securely, and globally, without the interference of traditional banking systems.

16. Simplicity Will Always Win

In the midst of chaos - simplifying your data solution will always win. Focus on the fundamentals and delivering a simple data product that produces maximum business impact.

17. The Unified Data & AI Ecosystem

Organizations will set out to design a unified data architecture across the organization. This remains a noble ambition - whether you call that an Analytics Hub, Data Mesh, Modern Data Fabric, Cloud Data Repository, or even a Modern Data Warehouse.

18. Cultivating Lasting Stewardship

Data Governance missions have long been impossible - for various reasons. Many have bravely died upon that mountain. In coming years, stewardship of Data & AI solutions will be critical to their success. Empowering the business stakeholders to take ownership of their AI products, validate business process, and drive business value alignment.

19. Change Is Inevitable

And when Microsoft changes its data stack - it has a ripple effect on the rest of the industry. And Microsoft will continue to bundle all of its Data & AI applications inside Microsoft Fabric. We expect this to have a ripple effect on the rest of the industry.

20. Window for Cloud Optimization

Let’s cut right to the chase - last year forced everyone to monitor/reevaluate their cloud spend. For some companies it was ugly. This year is a great time to reduce cloud costs by centralizing your cloud assets. Perhaps with the hope of reinvesting some of that savings into AI innovation.

21. Embrace Failing Forward

“This is how we’ve always done it” is probably a more dangerous sentiment than at any other point in the last 40 years. Organizations need to be embracing cloud data modernization and finding controlled ways to fail forward with AI innovation.

22. Custom AI Development

Every company wants a “crystal ball” to run their business. For those companies that have the resources, start small and build out the core. Prove the ROI back to the business and then build the next layer to the crystal ball. Rinse and repeat but never gloss over the business impact/validation at each stage of the process.

23. Continued Advances in Artificial Intelligence

It’s impossible to imagine where AI will be in the next 20 years. There will be continued innovation in Advanced AI, Quantum Computing, Adaptive AI systems, Computer Vision AI, and even advances Neuro-Symbolic/Emotional AI. In the meantime, most of us should focus on mastering the data-driven tools we have at our fingertips.

24. First Mover AI Advantage

In 2000, the average American household had internet access. Today we have 5G internet in our pockets with access to almost all the information on the face of the planet.

We are still very early in the AI revolution, and companies that adapt quickly will find themselves with a competitive advantage.

25. Robots Will Take Your Job

This might be true - but it won’t happen in the next year. For now, focus on leveraging AI to do your job more efficiently and help inspire creativity and innovation. Understand what the technology can/cannot do well.

And when the robots do finally come for your job, you’ll be ready to fight back with some good old fashioned “human” intelligence.

If you want to discuss Data & AI innovation with our team of experts or plan out your next data analytics solution - please reach out to schedule a complimentary Data Strategy Session.