how are AI and ML impacting the workforce of the future?

Machine learningIndustry 4.0 is transforming organizational structure and the very nature of work as traditionally defined with some crucial technological breakthroughs. Modern businesses are embracing innovative technologies such as artificial intelligence (AI), machine learning (ML), analytics and big data, as digitization and automation make their way into day-to-day business functions. According to a global survey conducted by Infosys, 66% of firms surveyed are already leveraging AI to improve their business processes and nine out of 10 C-suite executives reported to have had benefited by leveraging AI applications in their business. However, as business leaders consider incorporating new technologies into their organization’s operations, they also have to consider the impact of these changes on their workforce.

Let’s consider four ways in which AI and ML related technologies are impacting workforce in the digital age.

1. improving talent acquisition cloud computing

Sourcing, hiring and retaining high performing talent is not only one of the top priorities of modern organizations but also one of the top challenges. Recruiters are constantly trying to adapt to evolving job profiles, changing preferences of the millennial workforce and the rise of gig economy, and new technologies are enabling them to do so. HRTech firms are helping employers leverage AI, ML and analytics to improve their talent acquisition and development process. An increasing number of vendors such as Hirevue, Talview, Gecko, etc. ensure better scheduling, screening and interviewing for organizations. AI-powered recruitment solutions such as Oracle HCM cloud used for predicting candidate offer acceptance are fast becoming popular with recruiters. Similarly, other AI and ML-enabled technologies are being adopted to drive hiring decisions and to simplify HR processes, especially for recruiting and onboarding talent.

2. shaping the organization’s leadership

Increasing use of AI and ML-led technologies, automation and digitization have a significant impact on the people, processes and leadership of an organization. In their response to a study conducted by Infosys, four out of five C-level executives agreed that their future business strategy will be informed through opportunities made available with AI technology. Thought leadership is evolving to reflect this and set the tone of change for the millennial workforce as technological advancements call for significant transformation in terms of thinking, behavior, skills and performance. Business leaders not only have to adapt to new technologies and processes themselves, but also promote change for their workforce to be ready for new business models and new ways of functioning.

3. reducing manual task load to increase productivity

increase productivityThe use of technology decreases human effort significantly in some areas, and AI and ML-powered technologies are no different. Manual and redundant tasks such as data entry, documentation, reporting, reverting to queries, speech analysis, etc. take up a significant chunk of employee time and energy across functions. They can lead to a drop in productivity, which eventually has a negative impact on the bottom line. Compare this to the time that will be freed up for more meaningful tasks such as innovation and strategic planning made possible by embracing automation. High performing businesses realize this and are moving towards automation, ML and intelligent digital assistance to improve their processes and enhance productivity. According to PWC’s Economic Outlook for 2018 study, the main contributor to the UK's economic gains between 2017 and 2030 will come from consumer product enhancements stimulating consumer demand (8.4%). The study identified AI-driven technologies as a key factor for increase in productivity.

4. leveraging the power of big data and analytics

Computer systems that can think, learn and update themselves are gaining the attention of enterprises who are looking to automate their processes. Self-learning i.e. interpreting and analyzing the output from machine learning and analytics is enabling companies to move towards a predictive approach across functions. AI and ML are helping business managers access reliable data, generate valuable insights and take relevant actions in a timely and cost-effective manner. In a world of growing visual content, innovative firms are deploying AI and ML tools for data visualization and KPI tracking to produce automated visual reports. Hubspot, a leading name in inbound marketing, sales and service software providers, has incorporated machine learning and natural language processing in its internal content management system to better identify trigger responses, pitch prospective clients and even serve existing customers.

As Gartner predicts, AI technologies “will be the most disruptive class of technologies” over the next decade - business leaders are already considering ways to encourage their workforce to adopt them. Of the global leaders surveyed during the Infosys study, 50% reported that AI technologies will have the most impact on an organization’s operational excellence, 48% said that they will affect their ability to be responsive and agile, while 46% said that it will impact their ability to be competitive. It is clear that the adoption of intelligent technologies and data analytics is no longer a ‘why’ question for modern firms, rather, a ‘how’ question in terms of approach, strategy and organizational planning in adopting these new breakthroughs.


Source
https://emerj.com/partner-content/the-impact-of-ai-on-business-leadership-and-the-modern-workforce/
https://www.peoplematters.in/article/career/heres-how-ai-ml-and-robotics-are-shaping-talent-management-18103
https://www.infosys.com/age-of-ai/Documents/age-of-ai-infosys-research-report.pdf
https://www.cmswire.com/digital-workplace/5-ways-artificial-intelligence-will-lighten-employee-workloads/
https://callminer.com/blog/smart-implementation-machine-learning-ai-data-analysis-50-examples-use-cases-insights-leveraging-ai-ml-data-analytics/ 
https://www.smartdatacollective.com/machine-learning-business-transform-modern-workforce/