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Understanding Why Analytics Is Central To The Success Of Artificial Intelligence In Enterprises

Understanding Why Analytics Is Central To The Success Of Artificial Intelligence In Enterprises

Richa Bhatia

Analytics is a strong driver of AI strategy and digitally mature organisations that have successfully deployed AI have robust analytics practice. New survey findings from SAS, a leader in analytics, business intelligence and data management software and services, indicate that successful adopters of AI see a strong connection between AI and analytics. Interestingly, most AI leaders see the two as being inextricable from one another. Among the survey respondents, 79 percent of companies report having real success in deploying AI-based technologies also say analytics are expected to have at least a “major” role in AI.

Overall, enterprises that deployed AI are far more likely to say that analytics will play a “full and central role” in their AI plans – nearly half. Those who are merely considering AI, or whose AI capabilities are still under development, don’t see the connection nearly as clearly while roughly a third say analytics will play a “minor” role in AI – or no role at all.



A key finding robust analytics practice is in the organization can pave the way for faster AI adoption. Data and analytics will play a central role in the success of deployment of AI. Oliver Schabenberger, Chief Operating Officer and Chief Technology Officer shared that analytics has achieved a front and center role in AI. “In fact, in many ways, AI is analytics. Perhaps that is why 66 percent of respondents agree that AI will enable us to mine massive volumes of data faster to inform business decisions”.

From Analytics to AI

A large percentage of respondents said that analytics has a “major role” in their organizations’ AI strategy. Analytics drives the learning and the automation aspects of AI – a connection that may not be as clear among those who have yet to deploy AI successfully. Successful AI users show a level of maturity with data-driven processes that would be expected with successful AI deployments. With organisations advancing down the AI path, a robust analytics practice can help navigate the successful implementation of AI applications.


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Ethics in AI at work

The study further highlights how industry leaders are taking steps to ensure responsible use of artificial intelligence (AI) within their organizations. The study indicates more business leaders are taking steps to ensure responsible use of artificial intelligence within their organisations. For instance, AI adopters indicated relatively strong ethical processes in place today, with 63 percent affirming that they “have an ethics committee that reviews the use of AI,” and 70 percent indicating they “conduct ethics training for their technologists.” Most AI adopters – which account for 72 per cent of organisations globally – hold ethics training for their technologists and have ethics committees to review the use of AI. Leading tech giants Microsoft, Facebook and Google are leading the way when it comes to the development of ethics in AI. Business leaders are also following a more practical approach to ethics in AI with enterprises joining hands with academicians to set ethical standards. Another key insight from the survey is that ethics could be the guiderails and help develop best practices around this emergent technology. And successful AI adopters are already addressing important areas such as oversight, ethics and processes.

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In fact, last year our study by Analytics India Magazine and Cartesian Consulting stated that companies across various domains have extensively adopted analytics since the last year. It represented the extent to which analytics has penetrated in the domestic market, demonstrating that in every 59 employees in an Indian organizations, one was associated with data and analytics function. A key finding of the report was the negative correlation between maturity and penetration, stating how an analytics penetration doesn’t demonstrate a high maturity in analytics function. For example, while e-commerce firms have the highest analytics penetration of all sectors, they have the lowest maturity. In India Flipkart is the only company which is both high on penetration and maturity.

Conclusion

According to the Accenture report authored by Narendra Mulani, Chief Analytics Officer, Accenture Applied Intelligence, the emergence of artificial intelligence can help kick-start profitability. Accenture research shows that AI will boost profitability by an average of 38 percent by 2035 and lead to an economic boost of US$14 trillion across 16 industries in 12 economies by 2035. All in all, AI and analytics is crucial to the success of an enterprise’s digital transformation.

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