Navigating D&A Market Trends: Shashank Garg Explores AI’s Transformative Role in Data Analytics

Organizations should innovate with data and develop data fluency among their employees. While many businesses have dedicated teams focused on data delivery, the true value lies in employees actively utilizing this data. Data fluency is the organizational capability that allows staff to understand, access, and apply data as effortlessly as they communicate in their native language. When more employees become data fluent, productivity improves, employee turnover decreases, and innovation flourishes beyond just specialized teams. Companies should evaluate their data fluency and consider creating a data concierge system. This approach acts as a layered structure, enhancing data fluency and implementing measures to democratize data access and increase trust.

Furthermore, there is a significant opportunity to rethink how businesses leverage data to add value. Pioneers like Salesforce and Amazon have successfully developed Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) models, gradually shifting value delivery expectations from clients to service providers. The advantages, including agility, scalability, and broad reach, are well-recognized. In a similar light, data and analytics technologies must evolve towards productized services, which we refer to at Infocepts as Solutions as a Service.

The Solutions as a Service model combines products, problem-solving, and expertise into a user-friendly format. Given the rapid technological advancements, this new category necessitates a shift in perspective, providing a competitive edge akin to what early cloud adopters gained over the past decade. Infocepts offers various domain-specific as-a-service solutions, including e360 for people analytics, AutoMate for business automation, and DiscoverYai (AI-as-a-Service) to harness the benefits of artificial intelligence.

AI is generating considerable excitement. It holds real potential for the data and analytics sphere, especially in enhancing user access to data. Traditionally, business users faced challenges accessing data and often struggled with formulating the right questions to ask. AI can serve as both an accelerator and an educator, guiding users in comprehending what to seek in their data.

AI-driven insights can reveal the underlying reasons within data. For instance, augmented analytics can help uncover why certain sales are rising and identify variances in market penetration across different locations. Similarly, chatbots and natural language processing (NLP) solutions can interpret queries like, “What are sales for each category and region?” Modern computing capabilities, along with AI’s power, allow these tools to conduct numerous analyses within seconds, utilizing automated machine learning to identify the most suitable models and deliver insights to address business inquiries.

Moreover, AI can produce insights in a user-friendly manner, answering questions users might not have considered. With user input and machine learning, AI becomes increasingly adept at identifying which insights yield the most value. Beyond insights generation, AI can enhance data management processes through automatic data discovery, classification, metadata improvements, data governance, anonymization, and more.

On the infrastructure side, machine learning models can be employed to tackle classification, prediction, and control challenges, automating activities and enhancing capabilities such as predictive capacity, intelligent alert management, and anomaly detection.

So, where can AI create immediate benefits for businesses? For instance, in the retail sector, applications such as store activity monitoring, order management, and fraud detection have existed for years but can now be executed much faster through AI. In media, we help clients with demand forecasting, content personalization, and recommendation, as well as synthetic content generation for both text and multimedia. The banking industry is also witnessing wide-ranging applications, particularly in fraud detection, where AI not only identifies threats but also implements real-time preventative measures.

At Infocepts, we have adopted AI to enhance our productivity and employee engagement. Our HR team has introduced ‘Amber,’ an AI-based bot aimed at improving the employee experience. We utilize AI-driven assistants to document, transcribe, and track actions from voice conversations, while our marketing teams leverage generative AI tools for content creation.

The technological advancements experienced in recent years will soon parallel employee capabilities in the coming years, with AI-assisted solutions playing a pivotal role in this evolution.

For business leaders eager to begin their AI journey, my advice is to adopt an AI-first mindset. This means moving away from the conventional method of tackling complicated business issues through prolonged data analysis. Instead, embrace AI-driven auto-analysis that can reveal hidden patterns and insights much quicker, ultimately aiding teams in decisive actions.

Additionally, be prepared for some experimentation. Mistakes should be seen as learning opportunities, and initiatives such as hackathons and innovation contests can help generate ideas, embrace failures, and promote faster success. It’s also crucial for your team to develop a solid understanding of data, ensuring they can interpret AI-generated actions with confidence. As you employ AI, focus on making these solutions explainable and transparent.

Finally, establish systems to ensure your AI models stay relevant in a constantly evolving landscape. Continuous training of these models will prepare them to tackle increasingly complex challenges.