I recently read an article by Forbes titled Which Analytics & BI technologies will be the highest priorities in 2019.
In summary the main points in this article are as follows:
· 82% of enterprises are prioritizing analytics and BI as part of their budgets for new technologies and cloud-based services.
· 54% say AI, Machine Learning and Natural Language Processing (NLP) are also a high investment priority.
· 50% of enterprises say their stronger focus on metrics and Key Performance Indicators (KPIs) company-wide are a major driver of new investment in analytics and BI.
· 43% plan to both build and buy AI and machine learning applications and platforms.
· 42% are seeking to improve user experiences by automating discovery of data insights and 26% are using AI to provide user recommendations.
Based on what I see in the industry and what customers I speak to are focusing on, this is how I see these predictions being executed today.
1. 82% of enterprises are prioritizing analytics and BI as part of their budgets for new technologies and cloud-based services
On a recent trip to Australia, I engaged with 40 CFO’s in an event, specifically focussed on Analytics, Machine Learning and AI in Finance. A significant number of them expressed interest in moving away from using spreadsheets to analyse their business and were all looking at putting analytics at the forefront of finance. They saw Analytics delivered on the cloud as a clear way that they could ‘start small’, prove value and grow an Analytics platform from finance, to be a companywide platform for making business decisions. A majority of them were starting such initiatives in their organisations or were looking to start such initiatives in 2019. This was a mix of companies from large corporates to smaller enterprises.
So I believe that companies are prioritising investment in Analytics in 2019.2. 54% say AI, Machine Learning and Natural Language Processing (NLP) are also a high investment priority.
The narrative I hear from customers I speak to is that Machine Learning, AI and NLP investment is not a "maybe", but a "when" in their project roadmaps. Finance executives in particular see a large benefit for applying these technologies in finance to free up time from performing menial, low value tasks manually and getting machines to do those, so finance professionals can perform more high value tasks. Machine Learning and AI will be more prevalent in tasks such as Account Reconciliation, Predictive Forecasting, Expense Fraud etc.
3. 43% plan to both build and buy AI and machine learning applications and platforms.
Many of our customers who have adopted the latest Cloud Applications and Cloud Platforms from Oracle are seeing a great benefit by easily accessing AI and Machine Learning technology. Oracle is imbedding AI and ML into is Cloud Applications allowing them to consume the latest capabilities using machine learning and AI in the applications seamlessly. They are also automating or enriching some business processes by using Machine Learning capabilities, built in to the Analytics platform, aimed at business people. These capabilities make it easy for the customers as they negate the need for writing models in Pythion or R or even the need for a data scientist. Instead end users can use prebuilt platforms to execute models purely by using their data in combination with the delivered models.
4. 42% are seeking to improve user experiences by automating discovery of data insights and 26% are using AI to provide user recommendations
I also see a lot of our customers using the Machine Learning capabilities in Oracle’s analytics platform to help them analyse bigger sets of data and help them uncover trends, anomalies and patterns in their data they have not been able to discover before. We have done some incredible work with the NHS to help them analyse data across 10 different source systems to understand the true cost of patient care, care path of a patient and more information relating to the 4-hour breach.
My take on this is that the predictions Forbes mentioned surely resonates with what I am seeing in our customers. If you are not looking at creating a solid Analytics, AI and Machine learning strategy in your company yet, it should be something you prioritise. I am sure your competitors are.