FEATURE : MACHINE LEARNING
Issa said AI and ML are well suited in different verticals such as manufacturing , healthcare , telecom , public sector , retail , finance and automatise . “ If I select healthcare as an example , Artificial Intelligence is transforming healthcare in ways we never thought possible . And it really is all about data . Using data , AI and ML can help healthcare professionals make more informed , accurate , and proactive assessments and diagnoses . The ability to analyse data in real time enables healthcare professionals to improve the quality of life for patients and ultimately save lives . This will enable proactive diagnoses using smarter healthcare tools , help physicians find the right data faster and keep patients and healthcare organisations safe from cyber criminals and attacks ,” he said .
domain and data problems are managed by those closest to the systems . It is then for each domain to identify the opportunities they can apply to their data processes to introduce Machine Learning ,” he said .
Kevin Thompson , Cloud Operations Manager , Sage Africa , Middle East and Asia Pacific , said one of the key elements to consider is change management since ML and AI could potentially take over many of the tasks human workers currently execute manually . Thompson said businesses should look at how these new technologies can augment , rather than replace their people , and show people how the technology will free them from routine , repetitive processes so they can focus on work that needs more creative , strategic , or emotional intelligence .
Walid Issa , Senior Manager , Pre-sales and Solutions Engineering – Middle East Region , NetApp
CIOs and IT leaders should involve business to ensure buy-in for a Machine Learning system deployment in their organisation as that ensures success in the organisation .
Chris Royles , EMEA Field CTO , Cloudera , said CIOs and IT leaders will be influential in building and maintaining a data culture in the organisation . Royles said helping develop a data literacy programme and working across lines of business to instill the importance of data in each domain is an important start . “ We then suggest a democratised approach to data management where ownership of the business
According to Thompson , within a few years , ML will be so deeply embedded into every computer system that the industry will take it for granted . “ To get ROI , organisations should start out with a clear idea of the business outcome they would like to achieve and how they will measure success . For example , they might want to use Machine Learning to generate efficiencies in customer service . In this case , they could measure call centre volumes versus customers served by a ML / AI-powered chatbot . An insurance company could use ML for fraud detection and measure the value of the fraudulent claims the system picks up ,” he said . p
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