There is a lot of buzz around the corner about how technologies will emerge and behave in this new year and beyond, but only a few have acknowledged how such technological developments will impact the evolution of workers in 2020. Various companies across the industries are making new investments either in new technologies or workforce.
It is crystal clear that those who will acknowledge and embrace the modern working style with new-age workers, they will win against most of the inevitable challenge in upcoming years. This, however, subsequently means to disrupt and challenge the existing business models and ethics in order to streamline the processes and free up workers to focus on more innovation. With the rise in technology, the appetite of workers has also accelerated to grab more opportunities to thrive ahead.
We always think about how workers can match the ever-evolving capabilities of technology, but Verdict noted the views of industry experts who are more focused on answering whether they feel technology is rising to meet the needs of the future worker. Let’s explore what these experts have to say:
Role: Area Vice President – International
Company: Unravel Data
Views: Making data work for you in 2020
The transition of core business processes to the cloud has been the key business-technology trend amongst organizations for several years now. This is only expected to continue as more marginal data workloads are discovered to make operational sense to move off-premises. We saw in 2019 that business functions like CRM or HR made that transition and this will accelerate as more big data functions can make the jump.
That being said, another trend starting to develop in the second half of 2019 that we expect will proliferate in the new year, is AIOps. The fundamental promise of AIOps is to enhance or replace a range of IT operations processes by combining data with AI. Like cloud migration, not only does AIOps have the potential to drastically reduce the cost of deployments, it can do so while improving performance. As organizations move into 2020 and review their business processes, one or both of these considerations will likely become a priority.
Views: Enhance your learning with AI
In 2020, we will see a shift towards Human+ AI. This type of Augmented Intelligence will empower people in organizations to make better and faster decisions by utilizing the wealth of knowledge from other team members and experts within organizations. Rather than taking in and retaining all information as equal, true AI will begin to mirror the way the human brain works – digging out what is important and forgetting less meaningful data.
Real learning is based on recognizing when something you thought you knew has become obsolete and in 2020, the most advanced AIs will distinguish themselves through what they learn to forget, rather than simply what they taught.
Role: Chief Group Operating Officer
Company: ONVU Technologies
Views: Empowering the human worker
AI can help streamline and speed up processes that take much longer for human operators to process, as well as improving the margin for errors by many factors. AI is a long-term investment that should learn and improve as it operates. Businesses will start to see returns on investments in 2020.
Role: Regional VP EMEA North
Views: Protecting critical infrastructure
Industrial companies will continue to shift toward AI-based solutions for the analysis of cybersecurity data. This is part of a broader trend of companies shifting towards automation as workforce challenges, costs, and security needs force them to consider tools that can automate tasks efficiently and effectively. AI and ML tools will leverage data – the new oil in cybersecurity – to augment or remove humans using analytics.
But industrial companies, in particular, are looking for ways to better protect their critical infrastructure devices, whose vulnerability has become more apparent in the past years given the growing number and increasing severity of attacks on power utilities and manufacturing plants. CISOs are hungry for tools that can help them with this problem and AI has the potential to flag anomalous activity that could point to an attack and analyze sensor data for a more effective response to security threats and even predictive maintenance needs.
Both of these are important because downtime in critical infrastructure environments can be catastrophic. AI is far from a silver bullet and requires extensive expertise and is still largely in early technical innings, but demand for it will grow in 2020 and beyond.
Views: Artificial intelligence will play a bigger role in prospecting
Prospecting, which means assessing the quality of a potential customer, is one of the biggest challenges in the sales process. In 2019, we have seen the software in the form of chatbots begin to make the first contact with leads and gauge the customer’s interest on behalf of the sales teams. Moving into 2020 we expect that chatbots, alongside other artificial intelligence solutions, will play a far greater role in aiding salespeople.
Chatbots are just one example of how innovative technologies are reducing the burden of menial tasks for workers and enhancing their existing processes through AI-generated insights. In light of these benefits sales organizations, as well as those in wider industries, are increasingly recognizing that AI has the potential to reduce costs and drive efficiencies. In 2020, we expect that this trend will only continue as enterprises recognize how much technology has to offer their respective use-cases.
Role: Senior Vice President of Product
Views: Self-service data science to the rescue
For years we’ve heard about self-service analytics capabilities and how they empower people to create insights and drive change. However, descriptive and diagnostic analytics – finding out what happened and why – is just the beginning. How do organizations address high-impact, future-facing questions, such as predicting what may happen next and prescribing the next best action? Historically these next steps in the analytic journey required data scientists with specialized model building skillsets.
Yet, research shows there are simply not enough of these individuals to keep pace with the advanced analytics needs of an organization. Introducing self-service data science platforms and practices will enable a broader analytic workforce to up-level their skillsets, build models in a code free-way and become the heroes who will fill the data science talent gap and drive advanced analytics within organizations forward.