Two distinct entities have emerged within AI applications – agents and copilots. Agents are the workhorses of AI, the epitome of automation, autonomously executing tasks and making decisions with minimal human input. Copilots on the other hand, have their role in the dynamic interplay of technology and human ingenuity. Unlike the self-directed agents, copilots are designed not to replace human decision-makers but to collaborate with them.
Copilots democratise data insights and simplify analytics for users. They form a symbiotic relationship with human data analysts, mostly functional users, in ushering in an ecosystem of collaborative data exploration.
With copilots built using Gen AI, data analysis is not confined to the realms of coding or technical expertise. Users can pose questions in natural language and receive insightful answers in a customisable and easily comprehensible format from the underlying complex set of data.
These data-driven insights automatically surface, proactively alerting users to potential issues and opportunities. The tedious and repetitive tasks that burdened analysts—data cleaning, transformation and visualization are now seamlessly handled by these copilots. This liberates the functional user, allowing them to dive deeper into their data for interpretation, unleashing the true potential of human creativity in the analytical process.
How do GenAI driven copilots help organisations transform to data-driven decisions? Here is a roundup of areas where it is valuable:
Enhancing Data Exploration and Analysis: A user can simply request a copilot to "Show me the trend in sales for the past year, broken down by region and product category" and instantly receive the visualisation in an interactive format. Using Natural Language Querying (NLQ), the models adeptly comprehend and respond to queries in business language, eliminating the dependency on technical expertise.
Streamlining Data Preparation and Visualisation: GenAI powered copilots automate data preparation tasks such as extraction, cleaning, normalisation and transformation. Further they can generate visualisations like charts, graphs, maps based on data analysis, uncovering important business insights.
Democratising Data Access and Analysis: Gen AI empowers non-technical users to independently explore and analyze data, eliminating dependence on data analysts or IT teams. This democratisation of access to data ensures informed decision-making across various levels of an organisation.
Proactive Problem Identification: Copilots can continuously monitor data for anomalies and patterns. This proactive approach enables the identification of problems in real-time, contributing to improved operational efficiency and effective risk management.
Scalability: GenAI’s scalability assures handling of large and complex datasets for data analytics. In step with business expansion, it can seamlessly adapt to evolving data requirements, proving to be an indispensable tool supporting the organization’s growth cycle.
Trends shaping the future of GenAI and BI
Three important trends are shaping the application of GenAI with BI. Let’s look at them in depth:
Generative Explainable AI (XAI):
As AI systems become more complex, understanding the rationale behind their recommendations becomes crucial for decision-makers. GenAI unravels the intricate reasoning behind the data insights, providing explanations that improve comprehension and transparency. Given the opaque nature of AI algorithms, this capability goes a long way in improving BI’s adoption in executive decision making.
Imagine a scenario where an AI-generated BI reports suggest a strategic pivot in market focus. Instead of blindly accepting the recommendation, professionals can turn to XAI to gain an in-depth understanding of why the system arrived at the suggestion. XAI lifts the veil on the decision-making process, breaking down the intricacies of the algorithm and showcasing the relevant data points that influence the outcome.
By enhancing trust and transparency, XAI instills confidence in the decision-making process, making AI-driven insights more accessible and actionable for BI professionals.
Real-Time Data Analysis and Decision Support:
In the current VUCA world of business where information evolves rapidly, the ability to provide immediate insights and recommendations has become a strategic necessity. It shapes the agility and responsiveness of an organization, which is critical for navigating change and leveraging emerging opportunities to stay ahead.
Adaptive decision support, where recommendations are tailored to the evolving nature of data streams, is a vital feature in GenAI’s integration with BI systems. When context changes, AI-driven systems continuously recalibrate insights, ensuring that decision-makers are provided with the most relevant and up-to-date information. This agility is particularly crucial in industries where market conditions, customer preferences and other variables fluctuate rapidly.
Hyper-Personalised Data Experiences:
Personalisation features powered by GenAI transform the user experience, turning data exploration and decision-making into an engaging journey. Going beyond traditional one-size-fits-all approach, it caters to the specific needs of individual users.
Using analysis of behavior, preferences and historical interactions with the BI system, GenAI copilots comprehend what each user values in terms of data insights, visualisations and reporting. Thereafter, the system crafts a tailored experience that resonates with the individual's needs, presenting details in a format that aligns with their preferred style and requirements. Whether it's adjusting the frequency of reports, customising the level of detail or incorporating specific KPIs, the system adjusts for each user.
In conclusion, the use of GenAI with BI and analytics in changing the way we deal with data. It's not just about technology—it's a big shift in how we use data, turning it into a helpful partner that makes our decision-making smarter and more strategic.
Authored by Anurag Sanghai, principal solutions architect, Intellicus Technologies.
