AI: Let's Collaborate

Far from being the job-stealing, world-dominating villain portrayed in science fiction movies and popular culture, artificial intelligence (AI) is going to be the number one way that collaboration between humans will be enhanced in the coming decades. Our recent study, AI & The Future of Work, discussed the ways in which AI-enabled technologies can enhance collaboration between humans, rather than the reason many of us find ourselves replaced by a bot in the not-too-distant future.
 
AI can streamline collaboration by automating tedious or repetitive tasks, enabling humans to focus their energy on more value-adding activities that require attributes like empathy, creativity, and intuitiveness lacking from machines. But what machines do bring to the table is superfast analysis, which will guide humans’ decision making like never before possible.
 
Imagine sitting in a meeting with colleagues discussing a marketing strategy, customer usage, or buying patterns for a product portfolio. AI can synthesize large amounts of disparate data and find patterns or insights not readily apparent or easily discoverable by humans. That frees humans to spend more time assessing better data, discussing options, and planning a path forward. In other words, AI doesn’t replace your people or substitute for their skills -– it complements and enhances their value.
 
Bridging Communication Barriers with AI
 
Businesses across the globe are on a constant path of adaptation and innovation –- and seamless collaboration among people is a major enabler of this transformation. Surprisingly, some companies already are deploying AI to improve human interaction in global, multicultural contact center applications.
 
Take, for example, any of the millions of sales or customer support interactions supported by business process outsourcers in low-cost countries. A lot of resources are devoted to helping contact center agents better understand customer languages, and even to mimic their accents and manners of speech. But for a speaker from a different culture, detecting nuances and emotion in a remote caller’s voice isn’t easy. And even if some agents “get it,” scaling and maintaining the successes of your best performers across large numbers of agents spread across multiple locations, shift patterns, and types of work is tough.
 
By recording, and sometimes transcribing, customer interactions, and then “training” AI to recognize patterns of speech that lead to successful and unsuccessful outcomes, a company can use scripts, training materials, and even real-time “pop up” help to improve agent effectiveness. It’s not even necessary that we humans can articulate what made the interaction successful –- we just need to use a branch of AI called natural language processing, or NLP, to “listen” to transactions that lead to a particular result so that it can learn and identify similar patterns in future. It’s like having your best-performing agents listening in and helping every single one of their colleagues tune into buying signals, identify hidden needs and upsell opportunities, or understand and respond appropriately when a customer gets agitated. That would improve outcomes for everyone: your staff, your business, and most importantly, your customer.
 
Amplifying Human Skills
 
Of course, introducing AI to a workforce will take some getting used to. It has the potential to free people from a lot of drudgery, allow them to see new possibilities and make more informed decisions, and complement their skills in myriad ways. To do that, however, AI needs people to identify where it can best be applied; change processes and gather data to better apply it; and pose the right questions and train it with examples to improve outcomes. That requires people to be engaged and to embrace the transition, not fearful that AI will eliminate their jobs. This will require leaders to, well, lead, their organizations in understanding AI’s potential. They need to communicate and educate their teams, and encourage them to learn and experiment with AI. If managed well, this transition could open new and exciting dimensions to traditional roles, and throw up great opportunities for people development, while simultaneously driving business outcomes.
 
This people-centric view will champion curiosity and experimentation, both as personal and organizational traits. The human skills -– uniquely human qualities like creativity, empathy, emotional intelligence, and entrepreneurialism -- will shape a significant proportion of the future workforce. So it’s somewhat ironic that the technology many fear will replace us -- or even threaten our very existence -- actually has the power to help people do more and to magnify their effectiveness. It may require people to change how they think and what they do, but the reward for doing so is more rewarding work and more valuable employees.