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In today’s age, the market is highly competitive and rapidly evolving.  Businesses are trying to exploit the data and analytics to gain some advantage. The primary set of data sources in this regard are the transaction recording systems like Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), Human Resources Management System (HRMS), etc. Businesses across the globe utilize these transactional data sources to understand the insights of business in terms of “What happened”, with an objective of achieving business growth with increased organizational efficiency. However, what remains unexplored to many businesses is the potential of the ‘parked data’ in these ERP-like systems when it comes to finding answers to "What will happen".

AI is the Answer

The answer to "What will happen" lies with technologies such as Artificial intelligence (AI). As per a recent Gartner survey, AI is now reported as the most impactful new technology among CEOs for the third year in a row.

The possibilities with AI are infinite. As the business leaders take on the paradigm, AI is the key to unlocking the forward-looking indicators from the data. AI can be implemented in traditional systems and used to AI-fy the processes that have long existed.

Barriers to AI Adoption

Gartner’s CIO Agenda survey has identified barriers for AI adoption under three  groups as Enterprise Maturity, Fear of Unknown, and Finding a starting point. The challenges like shortage of required skills, finding use cases, data availability and quality, long solution development cycles impede the AI adoption initiatives.

Business Analysis teams have struggled over decades to extract, transform, and load data from ERPs like systems and then use it in AI/ML applications after widening it with external data, which is time consuming, expensive, and often not real time analytics.

Standardization of Processes

ERP like transactional systems have helped organizations in implementing best business practices in their business processes. The business processes are integrated across functions and the transactions are governed through robust mechanisms, which ensure the integrity and quality of data.

These business processes on high level behave in a similar manner, generating a common minimum information across ERPs. If you take the “Procure to Pay” process as an example, it will have the same high-level steps of Purchas order, goods receipt, invoice creation, and payment which generate vendor information, purchase order information, item, rate and quantity information, payment information irrespective of the ERP system.

This similarity of information across ERP products helps creating a standardized input and develop an AI microproduct.

AI Microproduct is the way

Business organizations always love plug and play kind of solutions; however, the AI solution development takes a considerable time and effort to create the custom solution for the problem.

Business organizations also always want this plug and play application to be completely in line with their requirement just like a custom solution.

Any AI project needs the steps of Connecting to data sources and collecting the data, unifying and analysing the data, processing the data for learning and presenting the predictions in the required form for consumption. 

A use case-based AI microproduct which sits on top of ERP like systems and seamlessly connects with it to collet required data, unify it with relevant external data to widen the information domain will have the data pipeline ready as the structure of the required information and the underlying schema of the ERP product can be of a standardized nature.

The ability of the AI microproduct to develop, evaluate, select, and deploy the AI models or solutions without any human intervention through Automated Machine Learning makes the AI microproduct a very convenient and useful plug and play kind of AI solution.

Conclusion

AI Microproducts for certain use cases like “Demand Planning”, “Propensity to Pay”, where not so complex AI solution is feasible, will be a great start for many traditional organizations to get on the AI journey quickly and enjoy the benefits of digital transformation with AI and become a data superpower.

Author:

Anand Mahurkar, CEO and Founder, Findability Science


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Kavita Rao
Chief Marketing Officer

Chief Marketing Officer @Findability Sciences Inc., a leading award-winning Enterprise AI Company helping businesses worldwide realise the potential of data and become data superpowers. In my current role, I am responsible for driving the organisations’s growth and brand awareness targets using innovative and traditional branding & marketing programs.

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