Rajesh Murthy, Founder Architect & Vice President Engineering, Intellicus Technologies

Rajesh Murthy is the Founder Architect and Vice President of Engineering at Intellicus Technologies, a data integration and BI product company. Being the Founder Architect and VP of the company, Rajesh spearheads numerous responsibilities including Product Development/Design, Engineering, and Marketing and Sales.

 

When Covid-19 was first discovered, one of the first policy decisions most countries had undertaken was to implement strict lockdowns. However, economic planners understood the catastrophe of such lockdowns and their relative impact on different sectors of the economy. AI and business intelligence platforms were one of the key technologies that helped companies in minimizing the losses these lockdowns and COVID-19 would have incurred. 

COVID-19 has therefore reemphasised the overall scope and importance of AI and Business Intelligence. The trends and outlook for the current year (2021) were expected to focus more on actual results and not rely too much on ‘big data’ and concentrate on small and varied datasets to achieve analytics goals. In 2022, AI and BI will continue to transform the way we think about conducting business. But these two technologies have yet to reach their full potential, and what that means for companies in 2022 remains to be seen.

Smarter, Reliable, and Scalable AI

Traditional AI processes have relied heavily on the availability of historical data. The accuracy of predictions and forecasts depend on the quality and quantity of information available to the organisations. However, with the disruptions caused by Covid-19, one could imagine that historical data could be irrelevant. Future technologies are expected to run on small data techniques and adaptive machine learning. AI systems shall also be based on better security measures, and compliance with regulations will be encouraged. Hence, even for small and medium-sized businesses, the overall reliance on AI-powered applications is expected to increase. 

Operational Artificial Intelligence

For many organisations, delivering and integrating AI solutions with enterprise functions and applications is a complex process. Even though the ‘idea’ of implementing AI in functional business areas appears to be a great idea on paper, the overall implementation process could take a significant amount of time. To reduce AI failures, firms must efficiently operationalise AI architectures. This reduced operational implementation time would mean that companies unwilling to adopt the latest technologies would be willing to try.  

Data fabric as the foundation

Data integration takes a significant amount of time in the deployment of AI mechanisms in organisations. Data fabric as architecture will support composable data and analytics. Usage and integration of data will take account of new horizons. A few areas wherein AI and BI potential has been realised could witness results in the next few years. 

Rise of Engineered Decision Intelligence 

One of the shortcomings of existing intelligence mechanisms is the inability to make crucial decisions. The emergence of engineered decision intelligence takes account of conventional analytics to facilitate individual and sequence of decisions. This process also helps in grouping decisions in respect of business processes. This process could help in taking structured decisions within stipulated timelines.  

Data and analytics as a business function

Like the usual business functions such as marketing, accounting, sales, production, etc., data and analytics are expected to become an integral part of business processes and functionality. Data officers in the company understand the trends in the industry and could also help in the long-term decision-making process. This could further enhance organisational success as the decisions would be more informed and based on factual information. 

Augmented Consumer and Workforce Experience

Taking account of a traditional perspective, predefined dashboards and manual data exploration took most of the data and analytics dashboards. Data scientists and experts understood predefined questions, but this trend is expected to change in the future. These traditional dashboards shall be replaced by automated, conversational, mobile and dynamically generated insights. This means that the insights knowledge is no longer restricted to a particular individual within an organisation but is universally available. As companies look forward to creating data and AI literate cultures, different functions will be improved, and some monotonous jobs currently carried out by humans will be redundant. In the current scenario, AI-powered tools and programs have already started assisting various functions, including internal and external communication of an organisation. With such a culture within the organisation, the overall business functionality will be more dependent on machines. 

Conclusion

The year 2020 was challenging for businesses and societies due to a variety of reasons. However, despite the challenges, the year helped in leveraging technology on many fronts. There were several industries that adopted the latest technologies for the first time. Even though the pandemic induced a significant disruption in different industries, technology came up with ready solutions. From improving customer experiences, facilitating work from home, and improving the quality of education by digitalisation, technology helped easily sail through the challenging time. Adoption of data, analytics, AI, cybersecurity and other new technologies became an integral part of the organisational functioning, and the trend is expected to continue even in the future. The only difference is that the organisations have now seen the actual difference that the presence (or absence) of AI and BI could make in respect to general functionalities. 

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