Will AI really replace us? (part 3)
It is inevitable that customer service work will be heavily affected by advances in AI and this is likely to mean a reduction in the overall number of frontline jobs. There are a range of opinions on how rapidly this change will occur, but for anybody involved in the industry it is worth planning how to respond as far ahead as possible.
In this third and final exploration of the long-term implications of Generative AI in customer service (follow the links for part 1 and part 2), I’ve set out three priorities each for employers, employees and governments to get ready for the AI revolution in customer service.
Employers
1. Involve frontline teams in the change from the outset
My experience of implementing AI tools with customer service teams is that Customer Service Representatives (CSRs) are generally excited about the possibilities for AI to make their work more satisfying and less stressful, Yet poor communication and engagement upfront can lead to distrust about the company’s motives.
Involving CSRs in projects from the start, including the design of solutions, can reap outsized rewards from better adoption and greater benefits of the tools.
2. Invest in skills that help to create more value from AI
Leading companies are already starting to invest in training the skills that will be most valuable for AI-led customer service. These include:
Skills for using and shaping AI, like writing knowledge content, designing proactive customer service processes, and using analytics to understand and fix the root causes of customer issues
Skills for governing AI, like mitigating bias in AI models, and protecting bots from external attackers
CSRs are often in a good position to retrain into these roles because of their existing understanding of customer service processes.
3. Make intentional choices about outsourcing
Customer service outsourcing will also be impacted by AI:
It is typically less complex processes that are outsourced today, and these are more likely to reduce in volume due to automation
However, some processes that are more complex today may be simplified sufficiently to be suitable for outsourcing in future
In addition, there will be new tasks created by AI that could be suitable for outsourcing, for example: quality monitoring of the output of an AI model
Because outsourcing contracts run for 3-6 years on average, companies need to think now about thing like outsourcing scope, commercial models and data governance for the future.
Employees
1. Focus on technical skills
Many of the new roles in future customer service organisations will require enhanced technical knowledge. Skills like prompt engineering, data analysis and cybersecurity will all be in demand across industries. The great news is that it is easy to start learning using free resources on YouTube, and there are plenty of more advanced courses on platforms like Udemy, Coursera and LinkedIn Learning.
2. Or… Focus on empathy
An alternative choice is to grow expertise in building customer relationships. The frontline customer service jobs that remain will require the ability to handle more complex and sensitive subjects and CSRs will need to be adept at winning customers over. Gartner recently predicted that by 2027, 30% of companies will combine all post-purchase services into a unified customer-facing role.
Some companies are already considering that they will need to pay more for these kinds of skills in future.
3. Unleash your inner entrepreneur
Times of change are also times of opportunity, especially with Generative AI which has such a low barrier to entry. We have not yet scratched the surface on the wealth of new business models that Generative AI will create. Customer service professionals are often well placed to be entrepreneurs because they have spent a lot of time listening to customers and understanding their need.
Governments
1. Think locally
Whilst change across the industry as a whole may be slow enough on average to be manageable, there may be faster and more radical impacts felt in specific regions. Governments should focus on promoting skills developments in areas with a high concentration of contact centre jobs, like Florida and Texas in the US, the North East of England, Gurugram in India and Metro Manila in the Philippines.
2. Solve for the next generation
Many businesses are confident that in an industry with naturally high attrition, plus opportunities for reskilling, that the transition to AI-led service can happen without excessive large-scale lay-offs. The bigger challenge will be a reduction in the number of entry-level roles for new starters, meaning fewer apprenticeship opportunities to move into more senior or expert roles. Different education options need to be made available to support young people to join the workforce with more technical skills right off the bat.
3. Stay fresh on employment legislation
Many large government initiatives on AI are currently focused on the more existential challenges, preventing bad actors from using AI to threaten democracy and impinge on basic freedoms. This is of course vital, but legislators will also need ensure that regulations allow for well-balanced and productive relationships between employees and employers, considering such factors as: levels of surveillance, job security, avoiding bias in the workplace etc.
Above all, we must approach these new ways of working with sensitivity and empathy, recognising that everyone will be experiencing changes that might at times feel uncomfortable. As we seek to harness AI, we mustn’t let that obscure our own basic humanity.
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