By Anurag Sanghai, Principal solution architect, Intellicus technologies
The field of business intelligence (BI) is on the verge of a revolution. Emerging technologies have indeed
shown immense potential in streamlining the analytical process to set analysts and BI professionals free
from redundant tasks. Yet, it should be noted that the role of AI in data analytics stretches beyond the
realm of automation. The progress lies in the creation of an intuitive and human-centered approach to
deliver comprehensible insights and empower strategic decisions.
From automation to co-pilots: The dual role of AI
The evolution of AI and machine learning is shifting towards agents and co-pilot models where AI doesn’t
merely replace humans but augments and assists them in complex decision-making and creative tasks.
The distinction between AI agents and AI co-pilots hinges on their level of autonomy and the way they
interact with humans.
Agents are programmed with rules and objectives, allowing them to analyze situations, make decisions, and execute actions independently. They can initiate actions based on their programming or in response to
changes in their environment. This autonomy allows them to handle tasks previously done by humans, such as customer service queries or data analysis.
Co-pilots are designed for a more symbiotic relationship between AI algorithms and human analysts as compared to agents. They are designed to augment the human user in a collaborative relationship and enhance human capabilities by providing supporting information, recommendations, or completing strategic tasks based on instructions.
The increasing importance of GenAI for data analytics and BI professionals
The evolution of analytics and the need for transforming questions into insights are turning data analysts and BI professionals into strategic knowledge handlers who orchestrate information to create business value. Here’s how GenAI augments their capabilities and increases their value in organisations:
Streamlined data preparation: GenAI automates data cleaning, normalisation, and transformation to
save countless personhours spent on redundant tasks. Instead of preparing data, analysts can focus on
strategic analysis and insight extraction.
Rapid insights: The natural language interface in GenAI allows it to understand and respond to plain-
language queries. It eliminates the need for analysts and business users to learn complex querying
languages and get immediate answers to critical with comprehensive visualizations.
Pattern discovery: GenAI can analyze massive datasets and identify unexpected trends, correlations or
anomalies that analysts might miss due to human limitations. This proactive analysis can lead to proactive
action towards potential risks or hidden opportunities for business growth.
Data democratisation: Copilots make true self-service analysis possible for users across the enterprise.
This reduces the bottleneck of relying on specialised data or IT teams and the culture of data-driven
decisions can be promoted throughout the organisation.
The future of GenAI in BI and analytics
The GenAI-led disruption of BI is fueled by a confluence of technological leaps. Some technologies that
would lead this evolution are:
Real-time decision support: Gen AI can synthesize vast streams of information in real time to empower businesses to act upon the freshest insights. As real-time and streaming analytics architectures mature, GenAI’s capacity to uncover insights from live data flows becomes crucial for agile decisions. Imagine identifying a sudden sales decline in a specific region the moment it begins or capitalising on fleeting market opportunities. Such real-time intelligence enables proactive adjustments that were impossible with static reports to provide a decisive edge.
Explainable AI (XAI): XAI goes beyond “what" the model recommends and sheds light on the why
behind those insights. This transparency enables users to verify AI-generated results, understand potential
biases and collaborate with the system for ongoing improvement. It will play a pivotal role in building
trust and adoption within businesses. Without XAI, even the most potent GenAI models risk being seen
as untrustworthy and relegated to the sidelines rather than integrated into core business strategy.
Personalised analytics: Gen AI adapts to specific roles and needs of different users to personalise the BI
experience. Dashboards and visualizations can be dynamically tailored to highlight key metrics based on
the specific job role, a focused approach that saves time and fosters a data-driven culture.
As capabilities expand and the partnership between humans and machines deepens, dashboards will
increasingly become conversational to provide interactive narratives alongside visualizations. This
transformation on the horizon promises to reshape the science of data analytics and the art of data
presentation. The future of BI, powered by Gen AI, is about redefining the boundaries between human
expertise and machine intelligence to create a future where data unlocks its full transformational power.
