Artificial intelligence AI takes the lead over intelligent automation IA. Intelligent automation is the combination of "'robotic process automation and artificial intelligence to automate processes,'" according to a recent article on the topic in HR Dive, a publication for human resources professionals. Organizations that embrace intelligent automation may experience a return on investment of 200% or more, according to an Everest Group report cited by HR Dive. However, that doesn't mean organizations can expect a reduction in headcount, according to the report. In fact, projections of a reduction in workforce thanks to intelligent automation may be "highly exaggerated," the Everest Group noted.

These leaders are using AI to automate processes too complex for older technologies; to identify trends in historical data; and to provide forward-looking intelligence to strengthen human decisions. AI is making back office functions, such as tax and finance, do more with less and see into the future. Other AI use cases (PwC has hundreds, in every sector of the economy) include financial planning, medical diagnosis, customised retail offerings, and models of individual customer behaviour. Soon AI will transform transportation, manufacturing, media, and more. The place to start is with a business problem.

What do we mean by'Boring AI' and how can your business benefit from it? AI can solve a number of problems but the biggest area keeping the C-Suite awake is how to use automation and AI to generate business value, or new sources of revenue. Our report discusses how'boring' business as usual applications of AI can add more value than deeply technical solutions.

Only 38% of workers are confident in their skill sets in the face of digital transformation and newly emerging technologies, according to a recent survey of 1,000 U.S. consumers by Computer Generated Solutions (CGS), an applications, enterprise learning and business process outsourcing company. The survey, which focused on emerging workplace trends in the AI era, found that 24% of workers feel vulnerable but are waiting for their company to provide upskilling, while 22% feel somewhere in the middle and are attempting to keep their skills up to date through a mix of activities. The numbers also vary across professions -- 48% of professionals seek training on their own versus 46% of people in medical roles and 21% of people in retail roles. Training includes online self-taught courses, outside courses and YouTube videos, said John Samuel, executive vice president at CGS. Ideally, enterprises should aim at "providing not only self-learning tools, but also pointing employees to these places that are more available and are largely no cost," he said. Meanwhile, another AI report, by KPMG, on the achievements and challenges of AI across different industries, surveyed 751 U.S. business decision-makers.

We see the growth of people analytics at first-hand at Insight222, where we are now working with over 60 global organisations to help them put people analytics at the centre of business. In tandem we have also created a digital learning academy with myHRfuture to upskill HR in digital and analytics. For the last six years I have collated and published a collection of the'best' articles of the preceding 12 months – see 2014, 2015, 2016 2017 and 2018, and following are my choices for the 50 best articles of 2019. Those who have read the previous annual collections may note that the number of articles that make the cut has steadily risen. This is partly down to my inability to prune down to 30 or 20 - although it was hard enough to get it down to 50! Mainly though this recognises the increased number, variety and quality of people analytics and data-driven HR material now being published, which is another indicator of progress in the field. I hope that the articles selected will act as a venerable resource library for those working, researching or interested in the people analytics space. That is certainly the intention. I have arranged the 50 articles into twelve topics: i) Driving business value, ii) the future of work, iii) the future of the HR function, iv) ethics and trust, v) employee experience, vi) strategic workforce planning, vii) ONA, viii) diversity and inclusion, ix) organisational culture, perspectives and case studies from people analytics leaders, x) retention, xi) assessment and xii) getting started, as well as highlighting a few of my own articles from 2019 at the end. I hope you enjoy the articles selected, and if you do, please subscribe to my weekly Digital HR Leaders newsletter. Ultimately, people analytics should be about creating value – for leaders, for managers and for the workforce. So, where better to start than with seven articles that collectively provide insights on how to create value and/or give examples of where organisations have created value from people analytics.

RT @MaxDigitalSight: Consulting firm @Accenture reports that AI could double annual economic growth rates by 2035 by "changing the nature of work and spawning a new relationship between man and machine."

Deloitte today launched its Middle East inaugural Experience Analytics event in Dubai at Dubai Studio City. Experience Analytics is a globally recognised Deloitte event and has previously taken place in London, Amsterdam and Berlin. The theme is'Me, Myself, and AI' and brings together a combination of technology showcases and practical sessions that explore a number of topics across Analytics and Artificial Intelligence. It is not about people vs. machines but about how human collaboration and decision-making can be enhanced through the use of machines – this has been coined by Deloitte as the "Age of With". "We believe that we are entering an important phase for society in the Age of With, and in order to make a true impact that matters, we understand how important it is to collaborate and leverage our relationships with our alliances and eco-system partners to build the best solutions for our clients. Some of our global alliance partners for the event are Google, SAP, Informatica and Cloudera," said Rajeev Lalwani, Deloitte's Leader for Strategy, Analytics and M&A in the Middle East.

Most organizations use a variety of data collection and analysis methods to understand their stakeholders, whether through customer satisfaction surveys, product reviews, or employee pulse surveys. These ways of gaining insights fall into two broad categories: quantitative and qualitative data collection and analysis. Quantitative responses can be tallied and analyzed quickly, efficiently, and accurately with the help of mathematical logic formulas, algorithms, and, now, machines. Analyzing qualitative data is typically trickier, and it largely remains the province of human analysts, given that it requires a high degree of contextual understanding and social intelligence. For qualitative analysis insights to be considered valid--and taken seriously--the old-school method generally involves two or more people separately analyzing (for example, coding or categorizing) the data collected.

GlobalData research has found the top artificial intelligence influencers based on their performance and engagement online. Using research from GlobalData's Influencer platform, Verdict has named ten of the most influential people in artificial intelligence on Twitter during Q4 2019. Ronald van Loon is a recognised thought leader and one of the leading influencers of technologies including AI, IoT, big data, and data science. As director of Advertisement, now acquired by Digital Power, the influencer provides insights and secures analytics data quality, among other responsibilities. The influencer states that enhanced AI capabilities will allow drones to be controlled with the mind, along with robots eventually overtaking humans.

Rather than a tech-lash, what we're seeing is a tech-clash. People don't oppose technology; they remain excited and intrigued by it. But businesses are developing and deploying that technology using the playbooks of decades past, from the days before tech had such a major, meaningful impact in our lives. Closed ecosystems can make experiences disjointed. Artificial intelligence solutions are applied to decision-making without transparency, leaving people out of the loop on decisions that directly affect their lives.