Although corporate leaders have talked about skills gaps for years, the spread of automation and artificial intelligence is prompting some of the biggest companies -- including Amazon, JPMorgan Chase, SAP, Walmart, and AT&T, to name just a few -- to take action, not with small pilots but with comprehensive plans to retrain large segments of their workforces. These programs signal that the "future of work" is no longer an event on the distant horizon. Our latest research finds that the occupational mix of the economy is already shifting in ways that will accelerate over the next decade. Although we estimate that only 5% of all occupations can be fully automated, the activities in nearly all jobs will evolve. As intelligent machines take over many physical, repetitive, or basic cognitive tasks, the work that remains will involve both more technical and digital skills and more personal interaction, creativity, and judgment.
Human resource managers plan, coordinate, and direct staff recruitment and retention processes for organizations, businesses, and agencies. These professionals function as a link between employees and management. Large companies employ HR professionals as labor relations directors, compensation and benefit managers, and training and development specialists. The US Bureau of Labor Statistics projects a 9% increase in employment for human resource managers between 2020 and 2030, which points to a promising future in this profession. HR leaders should be in demand to navigate changing employment laws and cultures, along with complex healthcare and retirement plans.
The rise of artificial intelligence (AI) is one of the defining business opportunities for leaders today. Closely associated with it: the challenge of creating an organization that can rise to that opportunity and exploit the potential of AI at scale. Meeting this challenge requires organizations to prepare their leaders, business staff, analytics teams, and end users to work and think in new ways--not only by helping these cohorts understand how to tap into AI effectively, but also by teaching them to embrace data exploration, agile development, and interdisciplinary teamwork. Often, companies use an ad hoc approach to their talent-building efforts. They hire new workers equipped with these skills in spurts and rely on online-learning platforms, universities, and executive-level programs to train existing employees.
Machines are eating humans' jobs talents. And it's not just about jobs that are repetitive and low-skill. Automation, robotics, algorithms and artificial intelligence (AI) in recent times have shown they can do equal or sometimes even better work than humans who are dermatologists, insurance claims adjusters, lawyers, seismic testers in oil fields, sports journalists and financial reporters, crew members on guided-missile destroyers, hiring managers, psychological testers, retail salespeople, and border patrol agents. Moreover, there is growing anxiety that technology developments on the near horizon will crush the jobs of the millions who drive cars and trucks, analyze medical tests and data, perform middle management chores, dispense medicine, trade stocks and evaluate markets, fight on battlefields, perform government functions, and even replace those who program software – that is, the creators of algorithms. People will create the jobs of the future, not simply train for them, ...
The continued contribution of the drug development community toward improving the quality of lives of patients, researchers, and the public at large, is and will continue to be highly dependent upon the careful execution of strategies to make vast amounts of data meaningful and usable. This is achievable by pairing data with powerful analytics and then using those insights to develop safe and effective processes and products. Although the drug development enterprise is undergoing major transformation, literature about what the sector should do to support and prepare its workforce for these changes is scant. What follows is a discussion of original research conducted by the Tufts Center for the Study of Drug Development (Tufts CSDD) to address workforce development in the era of digitization. The research is primarily based on an in-depth discussion with thought leaders and senior executives. Tufts CSDD identified recurring themes for discussion in articles in academic journals and the trade press between 2015 and 2019. Discussion topics included: (1) challenges and opportunities caused by the sector's digital transformation, (2) skills and competencies of future drug development professionals, (3) new roles that are expected to emerge within drug development, (4) changes in talent recruitment and retention practices, and (5) the reshaping of corporate mindsets and cultures to become digitally proficient organizations.