How AI, Cloud Computing, and Machine Learning are Solving the Problem of Sourcing the Demand for Specific Skills
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ROI with intelligent automation is unprecedented and fast becoming the number one organization priority for leading innovative businesses but there’s a huge disconnect between the project outcome and the skills to getting there. A recent survey found that a startling 64p of organizations believe the digital talent gap is widening in India. This statistic is made even more troubling by the fact that 49per cent of employees are concerned that their current skill set will be redundant in the next 4-5 years, with 34per cent believing it will happen in the next year or two.
One pressing concern for the right skill-sets is not just the expertise to implement intelligent automation but how this automated technology can be used to replace the need for people and the desired skills. The Harvey Nash / KPMG CIO Survey 2018 sees 65per cent of CIO’s reporting a lack of talent holding their organization back from these key tends/themes and as a result for this talent shortage, 67per cent are planning automation to replace the need for additional headcount.
But How Can These Automated Trends Replace the Need for Sourcing These Skills?
A big umbrella that all these trends fall under is Robotic Process Automation and this is the design to automate rules-based, repetitive tasks performed by humans, with the potential to cut labour costs, increase accuracy and improve compliance with relatively modest investment compared with other major software deployments. Let’s be clear, this is not yet something that replaces human cognitive behaviours and like Ai, the set-up is pre-based human configuration relying on decision algorithms for specific inputs to action the decision for best output.
The considerations of replacing roles and skills via this automated technology are becoming more real especially when executives consider the huge cost savings from avoiding additional salaries, recruitment fees etc and CIO’s are experimenting very successfully throughout testing, service desk and development using this virtual workforce.
The “bot” or “bots” can be considered an additional headcount and working with existing systems, processes and applications to perform operations in areas such as Finance, Procurement and HR, emulating human behaviour and delivering according to PwC between 200 – 800per cent of ROI. A proof of concept built and implemented between 4 to 6 weeks and real examples demonstrated by the PwC report revealed the following:
Automated execution of applications using advanced business rules and reduced effort in account reconciliation by 30 – 40per cent
Automated creation of quotes and cancellations of orders. An 800 FTE replaced with 50 bots reducing handling time from 30 – 10 minutes and reduced costs by 80per cent
50,000 outstanding payments closed within an ERP system with no human interaction. 91per cent of open items closed in three days instead of three months.
A great example of customer service sees an embrace of RPA to manage receipt and response to customer queries resulting in 80per cent FTE savings, a reduction in turnaround time from 8 hours to 1 hour and an error rate of 0per cent
The customer service RPA piece above can be further improved when you consider the involvement of Ai. The Info-Tech CIO Trend Report with —Capgemini Digital Transformation Institute, “Turning AI into concrete value: the successful implementers’ toolkit showcases that the simplest customer facing chatbot can improve customer satisfaction by 10per cent over the course of a year.
Companies like Vodafone take the approach a step further and a recent expert webinar “Realizing the Digital OneOffice: Vodafone Embraces RPA and AI to Unify Its Employee and Customer Experiences” with Eric Fradet, Head of Innovation & Engineering, Vodafone Group Services Limited talks about the importance of intelligence and predictability of AI/ML technologies when unifying and improving customer and employee experience. Cloud is delivering real-time customer insights and invaluable data that if harnessed in the right way, could interpret and predict the customer to reshape their behaviour and buying intentions far beyond any human counterpart. During the webinar, Eric Fradet highlights that right now many are replacing skills with automated technologies in very static scenarios. A customer-facing chatbot will use the information only from the current inputs of the human counterpart and they are only against this received information. To be invaluable, the Ai systems must intelligently build up decision-based algorithms from multiple inputs including the current chat based information and then in parallel, lookups to the historical customer data file (if available), heatmaps of activities showing trends to the point in time this interaction is happening and future based predictions to set the reply back to the customer that delivers a chatbot response with added intelligent value…this is the value-add that is key to success!
These automated technologies are not without their fault and as stated earlier, we are not at a point that these technologies mirror human cognitive behaviour or empathy. They are not built without human intervention and they are only as good as the worse process that sits within your organization. To reap the reward, you have to ensure your processes are clean and updated.
The Accenture survey “The promise of artificial intelligence. Redefining management in the workforce of the future” reveals some fantastic findings supporting the automation of Ai working with managers including this popular trend augmenting 10 out of 11 management tasks. Whilst effective from a time perspective, we still see massive gaps compared to the human counterpart when embracing Ai for sourcing skills and an example around ethics can be sampled here in Computerworld with the Amazon recruitment engine. Unfortunately, Amazon’s experimental hiring tool used artificial intelligence to give job candidates scores ranging from one to five stars (along with the lines of how people rate their products) and the system was using historical data to base its algorithm decisions for the right candidate. The big problem is that the 10-year period from within the tech industry was going to be male dominant and when Amazon Machine-Learning specialists investigated the detail, they discovered that the Amazon system had taught itself that male candidates were preferable. Amazon’s Ai recruiter was penalizing resumes that included the word "women's," as in "women's chess club captain” and it downgraded graduates of two women's colleges, according to people familiar with the matter.
The Great Impact
The impact of intelligent automation with skills comes from Machine-Learning expert Andrew Ng with the AI Transformation Handbook Andrew talks about the mistakes we saw with the emergence of the internet and how shops launching websites did not make them an internet company because they did not leverage all opportunities that the internet had to offer.
This same approach can be taken with intelligent automation for replacing the desired skills gaps.
Any typical company + deep learning technology ≠ AI company
“For your company to become great at AI, you will have to organize your company to do the things that AI lets you do really well” – Andrew Ng