Most employers do not feel threatened by artificial intelligence. According to recent data from work benefits giant MetLife, 56 percent of employers demonstrated a positive view of automation technologies like artificial intelligence (AI), analytics and even robots. In contrast only 20 percent of the 2,501 benefits decision makers surveyed said they were pessimistic about the impact of AI and its impact on their role in the enterprises. The aforementioned data came from their recent report, the MetLife 16th Annual US Employee Benefit Trends Study.
Employees too reported optimism about the future of automation. Of the employees surveyed for the study, 49 percent said they had a positive view of automation, while 24 percent had a negative view.
Their research conducted between December 2017 through January 2018 consisted of two distinct areas. The employer survey which consists of 2,501 interviews with benefits decision makers and the employee survey comprised 2,653 interviews with full-time employees, ages 21 and over, at companies with at least two employees.
Taking the two reports together, it seems clear that, at least for the moment, AI is seen as a positive addition to the workplace. It also likely to stay as a positive influence for the medium and even long term. Here’s six reasons why.
Related Article: 8 Examples of Artificial Intelligence (AI) in the Workplace
1. The Rise Of Self-Learning Enterprise AI
Ajay Khanna, vice president of marketing at Reltio, a data management company based in Redwood City, Calif., said that while there is quite a bit excitement about the prospects of AI and machine learning (ML), most companies are still not ready for any serious level of cognitive computing. “The key challenge is the quality of the data to attempt such an endeavor. Machine learning requires a reliable data foundation to ensure that algorithms are acting on the right information,” he said.
One challenge, not just for machine learning, but for advanced analytics in general, has been the tediousness of synchronizing data models between operational applications and data sources, and downstream data warehouses and lakes that are being used as the data catalog for ML. Ensuring reliable data requires blending and correlating profile attributes across disparate siloed sources, applications, and formats.
In the longer term, he said, enterprises will move towards self-learning enterprises, which requires making sense of the output from machine learning and advanced analytics and closing the loop between insight, action, and outcomes. “A continuous feed of reliable data, relevant insights and recommended actions generated from AI/ML provide additional value to have a closed loop where users can contribute to data reliability, and improvement of business processes and customer experiences,” he said.
2. AI-Driven Personal Relationships
The use of AI will not be limited to data and enterprise development. According to Shervin Khodabandeh, partner and managing director with Boston Consulting Group, it could also be used to predict success rates for human relationships. Relationship bots powered by AI could be used in predicting the success of human relationships, trustworthiness, and other qualities that normally would be deciphered through personal and direct experience. This will also apply to the enterprise where AI will play a greater role in deciding the best candidates for specific roles, leaving HR to play an increasingly administrative role. “Facial and vocal analyzers could provide essential mood information for companies, helping to further optimize business decisions. One example where emotion recognition can benefit companies is in customer service,” he said.
He added that start-ups that focus on any one segment of personalization, either through superior user experience, proprietary data access, or ability to establish feedback loops so more and more can be learned about everyone, are poised to attract some of the highest levels of VC funding for AI businesses.
Related Article: 7 Ways Artificial Intelligence is Reinventing Human Resources
3. AI For 'Heavy Lifting' (Big Data and Number Crunching)
Katrin Ribant is chief solutions officer and co-founder of New York City-based Datorama, which provides an end to end marketing integration platform. She says that while AI is still only in its nascent stages of development there is already a lot of AI being used today in very specific areas of focus, including fraud detection, billing systems and data integration. This is likely to increase as time goes on.
“From present day to the next three years, I foresee a lot of educating to aid the understanding of what AI really is capable of and how it can serve as a complement to business professionals,” she said. “For years now there’s been a bit of pushback from people who have been sold on the narrative of man versus machine rather than man plus machine. In the near term I see this thinking fizzling out as businesses begin to leverage AI to take care of the “heavy lifting” involved with number crunching and data wrangling.”
Five years out she believes there will be widespread adoption. Although it’s a bit difficult to foresee what level people will be using AI to assist in their respective business challenges, it’s safe to say that AI will move from being something that’s considered advanced to something that’s considered the norm — five years down the road. Rather than just being tasked with doing the hardcore number crunching, AI will start to appear in other areas where it can assist professionals on the job.
That may involve software taking action — within a certain set of parameters — on behalf of a person so that the professional can spend more time allocating their daily routine to strategy over, say, doing manual data extraction.
However, ten years out is where things get interesting. “I believe we’ll start to see a greater shift in the way people work, the specific type of work they’re doing and how they spend their respective time. This will be driven by the power of AI,” she said.
4. AI as IT Disruptor
Outside of the enterprise, AI is quickly becoming a phenomenon in daily life, whether it’s staying organized with a virtual assistant like Siri and Alexa or relying on Waze/Google Maps for the fastest commute time to work, or tagging photos with Facebook’s facial recognition technology, Bob Friday, co-founder and CTO at Mist, a Cupertino, Calif.-based developer of a new wireless network, said. He points out that as with any major technology game changer, AI’s application in transforming IT will create winners and losers among vendors. In fact, it should become one of the tech space’s more fascinating disruptions in the coming years.
Silicon Valley, he said, is seeing the emergence of startups with fresh approaches to improving IT performance and efficiency through AI technologies. These companies are using innovations such as Natural Language Processing — which allows machines to understand and analyze human speech or text to allow enterprises to easily query and understand everything happening in their networks.
In addition, they are using machine learning, neural networks, and data mining technologies to proactively identify or predict problems, understand the cause and scope of anomalies, and recommend solutions, with the goal being completely self-healing IT infrastructures. “Ultimately, we will see AI evolve to the point that IT infrastructures are totally self-healing. Today, we have done a great job collecting data, classifying it with domain knowledge, and then using machine learning and other techniques to turn this information into actionable insight. But the next step is still ahead of us - where the network proactively and automatically corrects on its own,” he said.
Perhaps most significantly, they are doing this at a pace that simply cannot be matched by larger, incumbent IT vendors.
5. Enabling Development Of Top CX
Cork, Ireland-based Voxpro — Powered by TELUS International, is a provider of multilingual customer experience and technical support solutions. Its CEO and co-founder, Dan Kiely said that automation may be growing in adoption but its impact can benefits today’s workplace. He said that using automation in essential processes will free-up valuable people for more critical customer experience engagement. “Take for example, customer support bot technology — this automation tool doesn’t replace talent but helps organizations utilize its talent. Bots free your teams to move higher up the value chain and unleash their star power,” he said.
As a result, there will be a step-change increase in resolution speeds that will impact teams’ overall success. As companies harness the potential of automation to complement their support teams, these tools will handle the transactional duties, arming live teams with the details to create meaningful value. It can offer your business tangible metrics, but it’s your team that is the power behind meaningful insight.
6. AI as Data Access Enabler
Finally, Doug Bordonaro is chief data evangelist at Palo Alto, Calif.-based ThoughtSpot, which builds business-intelligence analytics search software. He points out that automation could potentially lower the bar for both access to data and ease of interaction, but that it will not be some silver bullet where suddenly everyone is relying on automated insights to inform every decision. “Even after adopting and automating AI applications, businesses will need to teach their organizations about what data is available, how it can be applied, and how it should be applied. That’s why internal data evangelism is critical to the adoption and growth of AI solutions and automation in the enterprise,” he said.
To bridge this gap, companies will invest in data evangelist roles, specifically focused on working across the organization to educate users about available solutions, the value of data-driven decision making, and how to change traditional workflows to take advantage of the new capability. ”As BI and machine learning start coming together — which is already happening — the promise of automation is becoming reality. But it won't happen automatically, instead evangelism, education, and an understanding of the business will become the new enablers instead of technical expertise.”