In an era where coding is becoming commoditized and AI is reshaping the analytics landscape, the role of the analyst is rapidly evolving. As the tactical becomes automated, value shifts to the architectural – those who can think in systems, design with empathy, and speak the languages of both data and business. This shift is not about doing the same thing faster; it’s about reimagining what’s possible when barriers to execution fade away.
At Aimpoint Digital, we recognize four key shifts occurring in analytics and business intelligence:
- Generative business intelligence
- Integrated analytics
- Low-code data apps
- Human-centered design
Let’s dig into each of these key shifts.
1. AI-Accelerated Delivery & Automated Insights
The arrival of Generative BI (GenBI) marks a turning point in analytics. From automating code to documentation and batch edits, AI is becoming a core partner in the analytics workflow by allowing analysts to create in seconds what once took days. A rapidly maturing facet of AI for BI is conversational analytics, where generative intelligence tools like Ask Sigma make data exploration more interactive and accessible through natural language. By enabling both business and technical users to query data in a conversational way, these chat-driven interfaces are ushering in a new era of self-service analytics that was previously out of reach.
And while today’s GenBI tools can automatically generate narratives, visuals, and dashboards, they often lack nuance and data visualization best practices. Data accuracy also presents a critical challenge for applying AI in BI. Without strong data governance and a well-defined semantic layer, AI is susceptible to returning incorrect outputs; undermining user trust and driving poor decision-making. Recognizing these limitations and anticipating what’s ahead is essential for shaping an effective AI for BI strategy. At Aimpoint Digital, we recommend identifying low-barrier, high-impact use cases first, and taking a crawl, walk, run approach to scaling AI initiatives. This builds early wins, accelerates momentum, and creates a strong foundation for broader adoption.
As we look further into the future, GenBI may soon autogenerate insights and dashboards that reflect complex requirements, design best practices, and prescriptive recommendations. Analytics workflows will likely become entirely agentic – automated from end to end but guided by human intent.
2. The Integrated Analytics Experience
People live in tools like Teams and Slack – so our analytics need to meet them where they are. Centralized analytics was the first step in BI modernization where users no longer combed through files but rather visited a single web-based BI platform. Then came embedded analytics which improved the user experience by publishing dashboards within websites, providing users with a more familiar and intuitive experience. Now integrated analytics is the next leap forward where dashboards and chatbots exist in the communication and collaboration apps we call home. This shift not only improves adoption but transforms analytics from something people visit into something intertwined with their daily ritual.
3. Low-Code Data Apps
Another shift underway is the convergence of BI and application development. Low-code and no-code platforms now enable analysts to build more than dashboards; they can architect robust business applications.
With the right frameworks, dashboards can trigger actions: send emails, update records, and automate workflows. They become operational tools, not just reporting surfaces. Even more powerful are standalone data apps. These tools are purpose-built for specific personas by combining data, UX features, and actionability into a single interface. This evolution expands the role of the analyst. No longer just visualizers, they’re becoming builders of digital products.
At the forefront of the data app revolution is Sigma – a cloud-native BI platform that empowers users to build interactive, scalable data applications directly in a spreadsheet-like interface – no code required.
4. Human-Centered Design in the Age of AI
While AI for BI can accelerate coding, streamline documentation, and generate baseline visuals and dashboards, it can’t yet make data visualization remarkable. That’s our job. Analytics products are not just functional, they're carefully crafted solutions, built to empower decision-making amid uncertainty. The real value lies at the intersection of data and human experience, where analysts combine technical delivery with user-centered, problem-solving design.
These professionals will continue to stand out in an AI-driven world by integrating metrics, features, and design with purposeful balance to create experiences that clearly answer the what, why, and next – driving actionable insights and deeper engagement.
Bringing It All Together
Even as we look to the future, we must stay grounded in the fundamentals. Flashy AI tools mean nothing without proper top-down initiative alignment, structured data governance, and change management strategies. And we can’t forget what got us here: a deep commitment to business partnership and high-quality technical execution. Tools like SQL, Python, and core BI platforms remain not just important but essential, and a well-designed semantic model remains the linchpin of a data platform and is the foundation of BI (and AI) success.
The leaders of this new era won’t be defined by their titles as analysts or engineers; they’ll be known as designers, orchestrators, and experience builders. Those who thrive will be the ones who craft intuitive, impactful products; faster, smarter, and in sync with how people truly work.
At Aimpoint Digital we stand as leaders of analytics, AI, and data application innovation, empowering organizations to navigate complex transformations with confidence. Our collaborative approach ensures we don’t just deliver solutions – we co-create them, aligning cutting-edge technology with your organization’s unique vision while helping you build the skills your teams need to become analysts of the future with AI.
Join me on July 16 for a virtual event, Rewriting the Rules of BI. At this event, I’ll join Sigma leaders Luke Stock and Luke Stanke (who are both well-versed in the evolution of business intelligence) to discuss the shake-ups we’re seeing in the industry and what’s coming next.
It will be a great discussion about the next wave of BI and where we see it going with data apps and AI. I hope you’ll join us.
