ARTIFICIAL INTELLIGENCE: MAKING WORK LESS ROBOTIC
Marco Ambrosio
Throughout history, disruptive technologies—like the car, smartphone, or drones—create an ecosystem of opportunity from emerging jobs to new or ancillary companies. If there are no drones, then there are no drone designers, drone mechanics, drone manufacturers, or future drone air traffic controllers. These examples are all physical and easier to comprehend than software or AI. Yet, AI is ever present. While AI has already and will continue to replace some jobs and create others, the majority of workers will continue to see components of their roles slowly shift as AI replaces low value repetitive tasks and supplements their work with others. In this way AI enables more rewarding work and opens up opportunities for greater employment stability, specialization, and higher pay.
AI is an umbrella term for the perceiving, synthesizing, and inferring of information by a machine using software algorithms. Narrowing the focus on one type or application of AI creates a better opportunity to understand core concepts and potential areas for business executives and policy makers to explore.
1. THE CONTACT CENTER: HOW DISRUPTION CREATES THE JOBS OF TODAY AND TOMORROW BUILT AROUND SOCIAL CAPITAL
The U.S. is an information and service-based economy where consumers and consumption act as the fuel that turns the gears. At its most basic level, it is a system of intents and the fulfillment of those intents. In this model, the faster a person’s intent— whether that is to purchase, to connect, to donate, to volunteer—is fulfilled, the more fluid and efficient the engine, economy, and society. An often overlooked but significant component in this machinery is Contact Centers.
Contact Centers are a front line for customer engagement. In the U.S. Contact Centers employ 2.79 million workers, over 1 out of every 50 American jobs in 2021. Contact Centers jobs are typically metric driven shift work with low pay, limited flexibility, high stress, and high burnout. The average annual turnover in a Contact Center ranges from 30-45 percent37 although it is common to see a company over 100 percent. The majority of these jobs do not require a college degree and the average annual salary for a Contact Center agent is $36,435. Contact Center jobs can be great stepping stone roles but in the majority of cases they are not a path to middle class income or stability.
The Contact Center industry is currently undergoing a massive transformation as Google, Amazon, and Salesforce among others have all entered the market to apply automation and AI at scale to help companies reduce costs, increase customer satisfaction, and better leverage customer data. These companies are focusing on the potential of Conversational AI, the ability for technology to process and understand the natural language people use and then take an action. It serves as a high impact, high value example of AI that the reader has likely already experienced. While first generation Conversational AI is for simple uses cases and command driven (e.g. Alexa play Queen or Siri set a timer for 20 minutes), the second and third generation focus on increased contextual understanding (e.g. memory recall and nonlinear conversations) and auto generated responses from pre- trained models or unsupervised learning methods (e.g. Jasper AI’s text to image generator or OpenAI’s GPT 3 speech responder). As Conversational AI advances, the potential for disruption and value to businesses, workers, and consumers looms large.
Increasingly people expect the ability to complete tasks or fulfill intents conveniently on their time—even asynchronously—and in their preferred channel (e.g. calling, self-service on a website, on an app, or via messaging channels like iMessage or WhatsApp). Industry leaders enable multiple channels and use Conversational AI to identify, aggregate, and measure the intents coming in from their prospects and customers and route accordingly to fulfill the intent. Low effort, simple intents such as check my status, reset my password, change my address, or schedule an appointment are routed to automations and fully contained at a low cost. No human directly interacts with the customer. More complex or sensitive intents may be greeted by an automation to help route the person to a specialized human agent. High touch consumer companies will even route by VIP or loyalty tier and savvier ones will geolocate, so a person is talking to someone in their same state or region.
By freeing up agents from the low value, repetitive tasks it allows agents to spend more of their time on higher value and more rewarding work. Research from LivePerson, a conversational AI pioneer working with Contact Centers, shows agents would rather help a person solve a real problem or higher value intent than basic, low level repetitive tasks. Agents report finding more meaning in their work. It is not a surprise that companies deploying Conversational AI solutions report greater than 40 percent reductions in agent attrition while increasing customer satisfaction by 20 percent.
Forward thinking companies enable automations and humans to work effortlessly together and use the hours saved to serve more customers, upskill labor for more specialized tasks, or move to increase personalization by offering new services like “guides” or “specialists” to improve customer experience. Likewise, they use AI to train workers with real-time recommendations or insights to shorten the ramp and time to productivity of the worker. Best in class companies also aggregate and track conversations across voice, messaging, and social channels for product or service optimizations or new ideas.
In the Contact Center, there are already new job titles like bot managers, bot testers and tuners, conversational analysts, conversational designers, and conversational engineers that are becoming more frequent and imperative if companies want to embrace being a conversational business or customer centered player. In many cases, it is upskilled Contact Center agents that are best suited for the roles. HSBC is one example of a large international company upskilling Contact Center talent into these roles as part of their pursuit to be a conversational bank and perhaps a model for other companies or public- private partnerships to follow.
The Task vs Jobs framework
The job titles mentioned above did not exist ten years ago, yet they are increasingly the roles of today and tomorrow. While some may be net new, most are previous jobs that have gradually morphed into a new job title as select tasks changed. There is tremendous dignity and intrinsic value of a job, but at its functional level a job is a compilation of tasks to be completed.
In the Task vs Jobs framework, the top 20 to 100 tasks can be mapped on a three- dimensional continuum across the repetitive nature (low repetition to high), required empathy level to complete each task (low to high), and strategic value of each task (low to high).This framework acts as a guide mapping out where to (1) use AI to remove repetitive, low empathy, low strategic value tasks off the task list of the job (2) use AI to support other tasks to be completed more efficiently or more effectively (3) increase focus or volume on tasks that are uniquely human. This process and shifting of tasks underpins the morphing of jobs and includes adding net new tasks that sit in this third bucket.
The Task vs Jobs framework showcases to business executives and managers the opportunities for AI to be a growth enabler rather than a catch all for cutting labor costs. For workers, it creates the ability to see how their jobs may shift, which tasks are most valued, and where to focus their skill development and time. The framework also creates clarity that empathy, emotional intelligence, communication, and problem solving become more important skills and assets for workers to future proof their careers and management to future proof their workforce. In all, these steps put an increased premium on, and reward, emotional intelligence and the soft skills required for social capital development.
2. MEETING THE EXPECTATIONS FOR ENGAGED CITIZENS
The consumer companies that grew out of the ashes of the dot com bubble understood and invested heavily in customer experience and technology. The more a company reduced friction in a customer’s journey from intent to fulfillment, the higher probability a prospect goes through the purchase funnel and the more likely they return to repeat the seamless process. The race to create better, easier customer experiences was on. The likes of Amazon and Apple to upstarts like Airbnb and Spotify used customer experience research, design thinking, and robust testing models to set high standards on customer experience creating a competitive edge by raising customer expectations. From 2017 to 2019, companies identified by Forrester Research as a Customer Experience Leader outperformed the broader market in the S&P index by 108 percent and CX laggards by 3.4X.
Raised customer expectations creates two important phenomena in the market. (1) Within an industry, it separates winners and losers as market share shifts. Hotels and short-term rental companies were forced to improve their customer experience and fine tune differentiators or continue to lose market share and revenue to Airbnb. (2) Perhaps not so surprisingly, consumers don’t live in one industry. They take their raised expectations a winning company has created (e.g. Amazon’s one click to purchase or same day delivery) to other industries including healthcare and government, historically two lagging sectors in the customer experience and innovation arena and arguably two of the most important for a healthy, engaged citizenry.
The wider the gap between two companies or two industries, the worse the perception to a person. The more friction in the process, the more people lose motivation to fulfill their intent. While it means winners and losers in the economy, for governments poor experiences and high friction limit citizen engagement, faith in government, and democratic participation.
As companies accelerate their shift to using AI at scale, the public sector will need to keep up to engage citizens, to increase scale and access while reducing costs, and to maintain a perception of effectiveness. The ability to complete services conveniently online, such as renewing your passport or registering to vote, is already a table stakes expectation for the American consumer.
Estonia is arguably the world leader with 99 percent of government services available online including voting, taxes, and accessing health data. Underpinning their success are major initiatives such as investing in free internet, launching a citizen digital identity solution with clear legal protections, and applying blockchain technology for data integrity. Similar efforts in the U.S. could enable citizens to access and to engage with government services and programs while satisfying the citizen experience expectations inherited from the private sector’s customer experience innovations.
The result could be increased participation and greater velocity between a citizen’s intent and fulfillment of it. Larger representative democracies, like Australia, are also making strong strides towards digital government transformation.
3. POLICY RECOMMENDATIONS
AI is a disruptive technology transforming multiple industries and jobs. Companies that view AI as an opportunity to expand and drive better customer experience and personalization will increase their advantage over competitors that replace workers at the cost of poorer services or widening customer expectations gaps. As shown in Contact Centers, workers can benefit in this model as replacing low value repetitive tasks with higher value ones makes jobs more rewarding and can reduce attrition creating more stability. Moreover, supplementing workers with supportive AI including real time coaching increases productivity, confidence, and skill development.
In the public sector, governments that use AI, such as Conversational AI, to increase access to public services, privileges, and rights, such as voting, will increase citizen participation and engagement. In a digital age, limited access directly impinges on a citizen’s ability to participate and use tools already budgeted for and available to them.
The launch of the National Artificial Intelligence Advisory Committee (NAIAC) by an act of Congress is a promising step. The committee has a wide-ranging remit but of particular interest will be their recommendations on U.S. AI competitiveness, developing the AI workforce, development and use of trustworthy AI in public and private sectors, and enhancing opportunities in diverse regions of the country. The recommendations should include ways to:
1. Further incent companies to invest more in R&D and upskilling talent through more accessible and/or larger tax credits to support the built out and scale up of new jobs, products, and companies. Velocity is important in the development of a new ecosystem as it lessens disruption and increases opportunity for workers.
2. Improve workforce resiliency and education by infusing school curriculums and adult training with emotional intelligence programs, growth mindset training, and foundational AI knowledge such as the Tasks vs Jobs Framework. Focus on public-private partnerships, for example, repurpose parts of struggling retail centers and malls for hybrid offline/ online reskilling centers; embrace non-degree accredited professional certifications for government roles.
3. Create a citizen digital identity solution with clear legal protections and a “Digital Bill of Rights”. Without these, both the citizen adoption and velocity of transformation would be limited.
4. Use AI in public agencies at the federal, state, and local levels to improve the citizen experience, to improve worker satisfaction and productivity in the public sector, to make access to public services easier and more convenient, and to increase participation in democracy.
Marco Ambrosio is an innovation and strategy consultant helping companies and teams optimize their products, services, and performance. Previously, Marco was an Innovation Executive at conversational AI pioneer LivePerson and a strategy consultant at Publicis.Sapient. Marco earned a M.P.H. from the Johns Hopkins Bloomberg School of Public Health, and a B.A. in Social Justice in Latin America from Fairfield University. He is a StartingBloc 2011 fellow.
