How Collaborative AI, otherwise known as a Hybrid Workforce, will impact the modern workforce.
Collaborative AI Defined
Collaborative AI is a new model of work that enables employees to perform their job functions faster and with more insight as a result of teamwork with AI systems. Otherwise known as a Digital Workforce or a Hybrid Workforce, Collaborative AI frees humans from mundane, repetitive tasks in order to focus on more high-value or unique tasks.
“In our research involving 1,500 companies, we found that firms achieve the most significant performance improvements when humans and machines work together,” according to a Harvard Business Review article on Collaborative AI. “Through such collaborative intelligence, humans and AI actively enhance each other’s complementary strengths: the leadership, teamwork, creativity, and social skills of the former, and the speed, scalability, and quantitative capabilities of the latter. What comes naturally to people (making a joke, for example) can be tricky for machines, and what’s straightforward for machines (analyzing gigabytes of data) remains virtually impossible for humans. Business requires both kinds of capabilities.”
With Collaborative AI technologies in place, companies will begin to reorganize corporate structures so humans can manage and improve upon AI systems that are performing basic tasks, such as data entry, answering common customer service queries, and more.
“[T]he introduction of new technologies can give rise to entirely new job categories,” write Jim Guszcza, Deloitte’s US Chief Data Scientist, and Jeff Schwartz, Deloitte Principal and US leader for the Future of Work. “In the case of call centers, chatbot designers write and continually revise the scripts that the chatbots use to handle routine customer interactions.”
Let’s examine two critical reasons Collaborative AI has become possible and how these changes will impact the modern workforce.
Conversational AI is Fully Democratized
We predicted 2019 would be the year technical novices could begin building AI use cases. With IT experts working alongside so-called “citizen developers,” users would be able to focus on specific use cases and flesh this process out while technology experts make sure the process is functioning properly.
Two years later, citizen developers no longer need technology experts looking over their shoulders. As we’ve seen with our Digital Employee Builder, AI use cases and fully-functional roles can be built and deployed in a complete process in less than 30 minutes, with no code required. As the year takes shape, more businesses will deploy AI systems using this no-code model.
We’ve seen this trend take hold in most other facets of the IT ecosystem. For example, 70% of enterprises already have policies in place for citizen developers, according to Gartner’s Citizen Development is Fundamental to the Digital Workplace report. By 2024, Gartner predicts more than 65% of application development will be from low-code development. This percentage could be even higher for Conversational AI.
Here’s why: As we detail in our white paper, A Beginner’s Guide to Conversational AI, not every business has the technical resources to create conversational systems using traditional implementation models. In fact, 47% of businesses say difficulty integrating cognitive AI projects with existing systems and processes is their biggest hurdle to AI initiatives, according to the Harvard Business Review. Companies also cannot find the talent required to integrate and deploy AI systems on their own. The same report revealed that fewer than half of businesses (45%) have a high skill level around integrating AI technology into their existing IT environment.
No-code Conversational AI systems will help line-of-business leaders with moderate or novice technology skills develop Collaborative AI use cases. These new systems will incorporate APIs, RPAs and visual components via conversational wizard-assisted design processes. By simply responding to the AI system’s suggestions and guidance— either through chat or voice-based conversations — employees will deploy Collaborative AI use cases mostly without help from the IT team.
The Corporatization of Conversational AI
Conversational AI “digital assistants” aimed at the general public (e.g., Siri, Alexa, Google Assistant), have empowered the average smartphone user to speak, rather than type, search-based queries. These experiences have been positive enough to persuade users to ditch the Google search bar in favor of conversing with Conversational AI. A survey from Pew found that 46% of Americans regularly use these digital assistants, with the most popular reason (83%) being the ability to “use a device without my hands.”
As the general public slowly becomes more accustomed to interacting with these digital assistants, information workers are operating alongside Collaborative AI systems — or Digital Employees — to perform business processes and to solve IT problems. These systems are more sophisticated than the digital assistants that people use to hear weather reports or locate movie times; they’re fully-trained workers who can process information, perform tasks, solve issues and collaborate with their human coworkers to help businesses run better.
Just as the consumerization of IT brought personal IT tools, such as email and chat to the enterprise, the corporatization of Conversational AI will see these more complex and intelligent conversational systems transition from the workplace into our personal lives. In fact, AI is predicted to power 95% of all customer interactions by 2025, including live telephone and online conversations, according to Servion Global Solutions. The ability to perform high-value commercial tasks through conversational systems is in such demand that 43% of millennials say they would pay a premium for a hybrid human-bot customer service channel, according to PwC.
For Conversational AI to move from the business into our home lives, users will have to rely on these systems to do more than report the weather. Businesses will have to allow customers to purchase products and receive white glove advice and recommendations through Collaborative AI. Insurance companies will need to empower AI to guide users through policies, make payments and even settle disputes. Banks will need to let users apply for mortgages or make changes to their accounts through Collaborative AI. The list of use cases is infinite.
We’ve already seen companies deploy these use cases to great success. As 2021 progresses, these use cases will become the norm, rather than the outliers, within their respective industries.