FEATURE : MACHINE LEARNING
Rider said it ’ s actually more about giving users the ability to use Machine Learning without building out or connecting technologies for years . “ Now we have platforms that allow quick experimentation and implementation so efficient ROI is quite real with the right vendor ,” he said . “ Some industries tend to be more progressive , such as industrial manufacturing , distribution and more . However , even within certain industries it ’ s more about the companies who aggressively embrace new opportunities and technologies that succeed . Those are companies that tend to continuously find new ways to pivot and expand their business , regardless of industry .”
Getting business buy-in
Stephen Gill , Academic Head , School of Mathematical and Computer Sciences , Heriot-Watt University Dubai , said to remain relevant and competitive , a CIO must adopt two positions within their organisation : guardians of infrastructure and digital catalysts of business value . Gill said as Machine Learning and AI continue to transform businesses across a myriad of sectors , organisations are gradually starting to see their huge potential . “ As with any initiative , stakeholder support is key for its eventual success and that is why so many CIOs focus on creating solid , evidence-based business cases for the technology investments that they want the management to approve ,” he said . “ While quantitativeempirical communications could be influential for other IT colleagues , CIOs also need to address non-IT stakeholders ( especially members of senior management ). They can do so by telling persuasive stories that illustrate the impact that the investment in emerging technologies such as Machine Learning will have on multiplying business value , especially on profits and revenue .”
He explained that being a good storyteller and a salesperson might not come naturally to a CIO who has risen through the IT and engineering ranks hence , it is important for them to develop such communication skills from their counterparts in sales and marketing , in order to gain the management buy-in and support needed to deploy their digital initiatives .
Challenges enterprises face
Priyanshu Vatsha , Intelligent Automation and Pre-sales Consultant , Proven Consult , said technical challenges associated with Machine Learning systems are majorly related to data . Vatsha noted that data unavailability , noisy , redundant or inadequate data makes it difficult to achieve satisfying results . “ Problems also arise if input data is biased or encrypted . Ongoing validation is an additional challenge for the implementation of Machine Learning models in practice ,” he said .
Vatsha said coming to non-technical challenges , building user trust is a big one . “ Users need to rely on them when facing the challenge of making important decisions . Legal requirements also often pose a significant challenge for a Machine Learning project . This relates to data privacy protection as well as decisions on who is going to be accountable for false decisions based on Machine Learning models .”
Dell Technologies ’ Richmany said Machine Learning is still in its very early stages and even at such an early development stage , the region is seeing it revolutionising a range of industries , with research and development advances being made in Machine Learning every day . “ For enterprises to ensure the success and ROI of Machine Learning deployments , it is important for them to align them to defined clear goals and use cases , and associate these to business priorities . “ Identifying and understanding whether the problems they are trying to solve could be tackled better and more accurately by Machine Learning rather than conventional software is key . Additionally , having experts run an elaborate experimentation phase of the potential projects which includes everything from gathering and assessing data , to basic modelling , cost and risk assessment can help predict whether the project will be successful or not ,” he added . “ This requires nurturing an organisation culture that values innovation . In the near future , we can expect quantum computing to significantly increase the capabilities of Machine Learning . It will give Machine Learning the capability to create systems that execute multi-state operations simultaneously . Quantum Machine Learning will have the ability to tackle complex issues in a split second .” p
Fady Richmany , Senior Director and General Manager – UAE , Dell Technologies
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