2025 was declared the “Year of Artificial Intelligence” and most organizations dipped their toes in the water – navigating the waves of AI readiness and literacy. While most people have already given up on their New Year’s resolutions by now - business and IT leaders are still asking the question, “Are we doing enough with AI?”.
Is Your Company Doing Enough with AI…
That’s a loaded question, that many organizations will be challenged with. It’s difficult to quantify what early gains or ROI have their AI initiatives produced. Weaving together a holistic fabric for AI innovation is both complex and requires near perfect alignment between business teams and technology innovators.
In this article, we’ll outline the 10 Frequently Asked Questions that companies are asking about Artificial Intelligence heading into the New Year.
What does “AI Ready” actually mean in 2026?
No, it’s not how many employees are using ChatGPT. It means having the infrastructure in place, to build a unified ecosystem for all your AI agents and services to access trusted and governed data, robust semantic models, and secure access to a suite of AI services. Platforms such as Microsoft Fabric enable companies to build their AI capabilities upon a unified cloud ecosystem. Technology leaders still believe AI will be revolutionary this decade. A recent survey from Harvard Business Review found a similar sentiment.
What specific business problem should AI solve first?
There is no question that the constantly evolving AI technology is powerful. But how can IT drive alignment among business stakeholders to identify use cases that truly impact the business. Data Science initiatives failed in the past because they couldn’t drive alignment with the business or persuade the business to trust the data. How can AI efforts avoid the same costly mistake?
What’s the biggest mistake companies make with AI adoption?
Let’s be honest, nobody wants to end up on the front page of the newspaper. Treating AI as simply a technology problem is a huge mistake. Successful AI adoption starts with executive alignment, trust in the data, and continuous enablement and education. Cultivating an AI-centric culture and establishing proper governance early on will pay dividends.
Have Hallucinations Been a Challenge?
How do we reduce AI hallucinations?
Your organization’s AI journey won’t always be picturesque. Building trust with business stakeholders starts with ensuring high-quality data and minimizing hallucinations.
Nothing will kill a project faster, than the executive stakeholders losing trust in the data. Building robust semantic models, deploying guardrails, and fine-tuning prompt engineering will go a long way in building a trusted AI organization.
What does an AI strategy actually look like & how do we get from POC to production?
Hiring a bunch of high-priced AI engineers probably isn’t the best approach. Stay lean and focus on producing a business outcome with the most efficient way possible. Don’t be afraid to fail and iterate – while inviting the business segment to share in this journey. Find a trusted partner, who can augment your existing team. Generally speaking, hiring large AI teams and using the “sexiest AI widget” is typically a recipe for disaster.
How do we measure the ROI of our AI efforts?
Prioritizing an AI effort based on business units can feel like an impossible endeavor. Ask these business units to help quantify the ROI metrics before you start building anything. High-value AI efforts usually target revenue growth, cost reduction, risk mitigation, or productivity gains. Focus on the ones that can be tied to a business KPI and where the ROI is measurable. The biggest ROI from AI doesn’t come from building models - it comes from building momentum.
How do we minimize fragmentation across our AI maturity model?
If every business unit picks their own AI platform – based on the flavor of the month - it’s going to create a nightmare for IT and create fragmentation across an organization’s AI initiatives. By leveraging an end-to-end platform like Microsoft Fabric, it will lead to better data quality, fewer points of integration, and lower total cost of ownership. More importantly, avoiding fragmentation will build trust across an organization and help an organization realize a tangible ROI.
Need Help with your 5-year roadmap?
What should our organization’s 5-Year Artificial Intelligence Roadmap include?
AI is here to stay folks – sit back and relax. It’s going to disrupt industries and professions that have existed for decades. Be adaptable to the shifting landscape, and embrace technologies that can solve immediate problems and long-term ambitions.
An AI roadmap should balance near-term wins with long-term platform, governance, and capability innovation.
How do we leverage Generative AI safely?
Everybody is using ChatGPT and we need to lock things down before this spirals out of control. Sound familiar? Enterprise AI prioritizes security, governance, integration, and repeatability. Begin building the policies and infrastructure that are secured with identity, access, and audit controls. Find the quick wins to introduce even basic guardrails and governance.
Is Microsoft Fabric really an AI tool?
Let’s be honest, there is a new AI tool that hits the market almost every day. Microsoft Fabric is a unified ecosystem that is comprised of a variety of AI tools like OpenAI, CoPilot Studio, Azure AI Functions, Azure Machine Learning, Azure AI Cognitive Services, etc. Fabric is an end-to-end platform that bundles all the data storage and data ingestion infrastructure. It also features Microsoft Purview to monitor data quality, lineage, and governance all in a single ecosystem.
Companies can also use Fabric Data Agents to autonomously discover, interpret, and act on trusted data—powering AI systems that answer questions, trigger workflows, and deliver real-time business insights with minimal human intervention.
I’m sure your organization is asking many of the same questions we outlined above. Weaving a fabric for AI innovation and aligning your organization on your AI maturity model is a great first step.
In this article from Forbes predicting AI trends in 2026, they also predict that AI literacy and organizational alignment are a key driver for success.
Organizations that win with AI this year won’t be chasing hype — they will be executing business-led use cases, measuring real outcomes, and investing in a unified AI ecosystem. The fastest way to get there is with a trusted IT consulting partner who can turn an AI strategy into scalable results.
**the last paragraph and all images in this blog were created with AI
