AI can be way off the mark in its answers to human queries. It can also be entertaining, such as in the recent headline-grabbing cases of DALL-E, which generates art based on user prompts, or ChatGPT, which similarly generates prose. It would be natural for contact center agents to view AI as a threat that could automate them right out of a paycheck. In live customer service, AI can handle many tasks. Those include agent assist, which plumbs knowledgebases for answers to customer questions via human prompts or automatically when listening to the conversation via speech recognition.

Here are three areas you should consider focusing on to set yourself up for success. Data scientists with the right combination of skills are in high demand. But what are hiring teams on the lookout for? As with many roles, both technical expertise and soft skills are important. As data scientist Vin Vashishta wrote, data science without soft skills has "limited value to the business".

Even before there was a coronavirus pandemic, boards ranked digital/technology disruption as their top business priority for 2020 -- followed by obtaining the talent needed to execute tech transformation. But COVID-19 has escalated digital initiatives into digital imperatives, creating urgent pressure on HR leaders to work with their CEO, CFO and CIO to rethink skills needs as business models change at light speed. It's no easy task for this cohort to identify and acquire the digital skills their organization needs to pursue digital transformation as imagined post-COVID-19. And now companies must press forward under a new reality: Technology skills are no longer highly centered in IT; they need to be "marbled" across organizational functions and businesses and coupled with soft skills to achieve transformation success. Most companies are flying "data blind" with regard to the skills they need for transformation Understand 5 key shifts in workforce trends and know how to turbocharge your response with talent analytics.

So-called'soft skills' would seem to be the most important foundation to build upon. These include things like the ability to communicate and work well with others, solve problems, and think outside of the box. Most of the universities and private colleges in Australia are now offering short courses, online or on campus, to develop these critical skills. Courses include critical thinking and problem solving, negotiation and interpersonal skills, and effective communication. We can't predict what all the job roles will be in the 21st century, but we do know that human skills will be in demand.

Five technology trends are poised to transform the future of work beginning in 2020, DXC Technology announced as part of an annual forecast. The rapid adoption of emerging technologies such as artificial intelligence (AI) and machine learning (ML) coupled with trusted data ecosystems, empowered interconnected teams and tech-evangelist leaders promises to produce new levels of workforce efficiency, productivity and growth across enterprises. "In turn, CEOs will seek to identify and pursue ecosystem-centric business models and trading partners that deploy trusted and compliant data-sharing practices." "The notion of accelerated productivity will force enterprises to rethink their technology decisions and investments across the enterprise technology stack, which, in turn, will drive a sea change in how enterprises are led and structured, make informed decisions and engage employees and customers," said Dan Hushon, senior vice president and chief technology officer, DXC. "Tech-evangelist leaders will define new interactions between AI and people to create high-performing teams and shape digital strategies that unlock an organization's full potential – securely and confidently modernizing applications, optimizing data architectures and moving workloads to the cloud to produce new and better business outcomes."

In the next three years, as many as 120 million workers in the world's 12 largest economies may need to be retrained or reskilled as a result of AI and intelligent automation, according to a new IBM (NYSE: IBM) Institute for Business Value (IBV) study. In addition, only 41 percent of CEOs surveyed say that they have the people, skills and resources required to execute their business strategies. The study, which includes input from more than 5,670 global executives in 48 countries, points to compounding challenges that require a fundamental shift in how companies meet and manage changing workforce needs throughout all levels of the enterprise. According to the global research, the time it takes to close a skills gap through training has increased by more than 10 times in just four years. In 2014, it took three days on average to close a capability gap through training in the enterprise; in 2018, it took 36 days.

In the next three years, as many as 120 million workers in the world's 12 largest economies may need to be retrained or reskilled as a result of AI and intelligent automation, according to a new IBM Institute for Business Value (IBV) study. In addition, only 41 percent of CEOs surveyed say that they have the people, skills and resources required to execute their business strategies. The study, which includes input from more than 5,670 global executives in 48 countries, points to compounding challenges that require a fundamental shift in how companies meet and manage changing workforce needs throughout all levels of the enterprise. According to the global research, the time it takes to close a skills gap through training has increased by more than 10 times in just four years. In 2014, it took three days on average to close a capability gap through training in the enterprise; in 2018, it took 36 days.

I worked at Amazon for 5 years, leaving just a few days shy of receiving the coveted "yellow badge." It's probably important to note that the average tenure at Amazon is anywhere between one to two years. While there are lots of stories out there about working at Amazon, I felt like the culture there did more to prepare me for my job switch from game development to machine learning than any tutorial ever could. If you don't know much about Amazon's culture, it's worth a quick Google search. Moreover, while I could probably write an entire book covering my experience there, I thought I'd focus on three things I learned that prepared me for this new career move: being data-driven, writing 6-pagers, and being resourceful.

AI, computational linguistics, computational vision, machine learning, and natural language processing skills receive some of the most eye-popping equity premiums. The following is a guest post by Kyle Holm (Partner, Pre-IPO Compensation Practice Leader at Radford) and Kelsey Owen (Director, Pre-IPO Compensation Practice at Radford). The race to build computers that act, see, speak, and think like humans is as competitive as ever. While some worry that artificial intelligence (AI) will someday lead to robots rampaging their way to world domination, AI-related startups have not stopped attracting intense interest from talent and capital. Just weeks ago, China-based AI startup SenseTime Group received one of the largest venture capital investment in the AI space -- a $600M Series C investment led by Alibaba.

Data science is fast becoming a critical skill for developers and managers across industries, and it looks like a lot of fun as well. But it's pretty complicated - there are a lot of engineering and analytical options to navigate, and it's hard to know if you're doing it right or where the bear traps lie. In this series we explore ways in to making sense of data science - understanding where it's needed and where it's not, and how to make it an asset for you, from people who've been there and done it. This InfoQ article is part of the series "Getting A Handle On Data Science" . You can subscribe to receive notifications via RSS. Enterprises are increasingly realising that many of their most pressing business problems could be tackled with the application of a little data science.