AI Predictions 2019: AI in Business Intelligence

Tom

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From a niche to the mainstream, recent years has seen AI technologies rapidly adopted to revolutionise business models and to optimise the efficiency of sales teams. AI-infused predictive analytics, spam filters and sales forecasting are several small examples of the way in which artificial intelligence is disrupting offices worldwide. Keep reading for the first instalment of my 2019 predictions for AI – democratisation, implementation and transparency included.

Business intelligence will accelerate with democratisation of AI

Over recent years, we have witnessed AI disrupt the business intelligence market on a revolutionary scale, with Gartner’s research showing that 85% of CIOs will be piloting AI programs through a combination of buy, build and outsource efforts by 2020. Accompanied by a new generation of AI-infused predictive analytics and intelligent dashboards, 2019 will see a continuation of businesses implementing artificial intelligence. The impetus driving the acceleration of the BI market lies largely behind efficiency: machine learning used within sales teams currently facilitates an increase in leads and appointments of more than 50%, cost reductions of 40-60% and call time reductions of 60-70%, thus minimising time spent on manual tasks and allowing sales teams to focus on customers within the business operation.

As machine learning continues to revolutionise business models and maximise the efficiency of sales teams, we can expect to see more organisations implement AI in 2019. The adoption of AI by businesses will be eased with increased accessibility: the democraticisation of machine learning is  lead by technology such as Google’s TensorFlow, which hosts programming environments such as Eager Execution that allow clients to interact with the platform like a Python programmer. TensorFlow’s open source machine learning technology will likely be evolved further in 2019 to become even faster and easier to use, while the ongoing democratisation of machine learning will be adopted by other companies to improve accessibility for all.

Consumers and businesses will unite in demands for transparency

The implementation of business intelligence promises to not only optimize sales efficiencies, but also offers to glean opportunity insights, generate leads and introduce intelligent forecasting. While the data offered by artificial intelligence is invaluable for sales and marketing teams alike, consumers are increasingly wary of how businesses are using AI for data and sales targeting. For example, the increased implementation of machine learning to perform advanced analyses and pattern recognition, allowing businesses to match data profiles or track consumer habits, is one aspect of AI that fuels privacy concerns.

There is no doubt that businesses are boosted by AI that enables teams to perform a variety of sales-enhancing analyses, such as completing Customer Lifetime Value Analysis to address declining customer relationships or learn from patterns of client success. However, the current uncertainty and lack of information surrounding AI is creating a ‘black box’ problem, causing many who hesitate to interact with foreign and ambiguous technology to continue to abstain from AI completely where possible. However, the tech-savvy sceptics will demand both businesses and politicians to increase transparency surrounding data handling.

Therefore, in the face of increasing pressure to be transparent about machine learning data usage, businesses will either champion demands for transparency or be forced to refrain from implementing artificial intelligence altogether in fear of doubtful customers abstaining or of possibly being liable if AI is deemed unethical in the future. However, 2018’s introduction of GDPR legislation has proven that tech can and will be employed in Europe on the basis of transparency and trust. Ultimately, driven by consumers and businesses alike, AI companies will recognise that transparency is necessary in order to garner widespread acceptance.

Conclusion

There is no doubt that AI will continue to develop exponentially to improve and maximise processes for businesses worldwide. However, in order to gain true widespread acceptance and implementation, it will be necessary for businesses and policymakers to employ measures to regulate the technology, ensure transparency and protect data handling. These are the major obstacles that must be faced in 2019, providing an opportunity for AI to revolutionise the business world.

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