Artificial Intelligence (AI) is not a new term bursting into our lives. During 2023, it has become “ready for mass usage,” enabling faster and more effective access to analyzed data in a human-readable format.
Leading institutes recently published interesting predictions about the topic.
1.Morgan Stanley concluded that more than 40% of the workforce might be affected by generative AI in the next three years.
2.Gartner predicts that by 2026, those organizations employing GenAI as part of their customer experience will achieve 10% higher CX maturity.
Let’s align the definitions to avoid confusing AI and GenAI.
GenAI – A broad label describing any artificial intelligence (AI) that can produce new text, images, video, or audio clips. Technically, this type of AI learns patterns from training data and generates new, unique outputs with the same statistical properties.
AI - The science of making machines that can think like humans.
With this trend “crowned” as one of the most disruptive technologies since the smartphone, I am most intrigued by two significant areas of impact:
1. The impact on professionals and the job market
2. The impact on customer experience.
This article is focused on the professional impact on CS professionals.
The Job Market
We can expect new tools and technology to perform our jobs faster and more efficiently, and in a more data-driven approach.
The benefits are clear:
1. We will have more time and can improve additional professional and personal (human) skills. These skills should be our “competitive edge” vs. the growing power of the machines.
2. We will make informed decisions as AI performs advanced data analysis, crunches the numbers, and supports forecasts. Professionals will have the “luxury” of having most of the tedious work performed. At the same time, they can focus on sharpening their decision-making and process, which is expected to be more accurate. This begs the question of whether the decisions and direction set by humans will be more complicated with a broader impact on organizations, customers, and their ecosystems.
At the same time, I encourage my audience to keep their “eyes and ears open” for the upcoming changes that GenAI will bring. Primarily, which skillsets are likely to be automated and, as such, offer better and faster outcomes than humans?
According to Morgan Stanley, the following skills will be effectively performed by machines:
· Information Gathering and Factual Search
· Content Creation
· Data analysis
· Project management – Monitoring tasks
· Tasks prioritization
· Teaching and Training
· Evaluating Information for Compliance
Does it mean we will not have authors, data analysts, and project managers in a few years? I highly doubt it.
I have published two 100% “human-made” books so far. Will I be able to write books faster? Why not. As I consider my next book, I will happily have a virtual assistant to help refine my thoughts, language, and writing tone.
The opposite aspect is the top skills that will be difficult to automate (according to Morgan Stanley):
· Management of humans
· Negotiation
· Assisting and caring for others (Medical staff, therapists, social workers, psychologists, etc.)
· Technology design
· Active listening
· Service orientation
· Persuasion
What does it mean for us?
I like using a framework that simplifies the change management:
PEOPLE-PROCESS-TECHNOLOGY
Technological advancements are happening and will create a new reality for professionals. Now, it’s time for a mindset change, leading to rethinking our desired skill sets. The next step is to plan our professional path, whether acquiring new skills or honing on existing capabilities that we should strengthen.
Then, we must adjust our way of working (our processes). This will be a mutual change driven by organizations and individuals.
Examples:
Training experts can assume a substantial part of the content will be created by GenAI. It will integrate product knowledge, support ticket information, and other sources, such as community and customer feedback, into structured training material. Then, GenAI tools can create AI-based clips and training courses. I imagine an emerging new training & community specialist/designer role who will supervise the process, configure the tools, and verify the output. Will humans still evaluate end-users feedback? I believe organizations will construct processes instructing the machine to redirect specific feedback to human inspection based on predefined rules.
Customer Success Manager (my favorite role)
Regardless of the complexity of the product, the target market, and the type of customers, CSMs will have to get used to working side-by-side with GenAI as existing playbooks will be partial to fully automated and executed by machines.
Examples:
· Onboarding
· Adoption and best practices
· QBRs/business reviews (for long-tale customers and partially for Enterprise/high-value customers)
· Reporting and analytics.
In the context of the above, CSMs can evolve into “Success Architects” or “Customer Success Consultants” that will harness the benefits of AI.
A few Use cases to consider:
Customer Insights
AI will analyze user interactions, feedback, and historical data to develop advanced customer and user profiles. These profiles will empower Customer Success to measure progress and outcomes and intervene when needed. For example, based on business and operational, those customers who are of high value and need additional human guidance, Success Consultants will offer personalized and tailor-made recommendations and solutions.
Customer communication
It is one of the most “burning” challenges in CS today. Digital CS practice is all about scalable, innovative, and targeted customer communication, which is effective and cost-saving. Not surprisingly, we now deal with a new type of customer service agents. These automated chatbots and virtual assistants are powered by natural language processing to provide instant and personalized support.
But there is much more to come.
I expect AI to flag sentiment and tone, which should trigger human intervention. This is where the CS consultant will be influential in resolving challenges and issues the machine might not be able to handle. Moreover, AI algorithms will have sufficient knowledge to advise optimal times for reaching out to customers, ensuring timely updates, for example, letting the CS consultant know in advance whether the customer has been informed about important feature announcements.
Health score and Churn prediction
This is already a work in progress, and many CS startups focus on automating an intelligent and data-driven health score and predicting the likelihood of churn. AI will be instrumental in improving customer health scoring models. There are standard factors, such as usage patterns, feedback, and support interactions.
Moreover, I trust AI to learn better about the customer's journey and their actual business outcomes to provide more accurate and real-time assessments of customer health. With this level of insights and domain expertise (which I expect CS consultants to have), they will be able to guide customers professionally, regain their confidence, and lead them to achieve their objectives.
Onboarding
Successful onboarding will be a crucial metric, assuming the customer can achieve the first-time value quickly and with minimum effort. AI can facilitate the onboarding process by creating interactive and adaptive learning experiences. AI-driven algorithms will analyze user progress, identify areas where customers may need additional support, and dynamically adjust the educational content to meet the type of organization and users.
CS architects, for example, will design and monitor such automated/semi-automated onboarding; in addition, they will define the exception rules, which will require human support, and verify with the machine whether they track the correct usage patterns and customer outcomes.
Change is coming, and we need to embrace it.
The internet changed our lives just before the beginning of this century, followed by the mobile phone revolution ten years later. With the Internet of Things (IoT), we will soon have many aspects of our lives connected, stored, and analyzed. This is where AI and GenAI come into play. This new super-fast train is about to stop at “our” station, and we must board it. In the context of customer success, I would like to have a partnership and synergy with AI.
Opportunity, not a threat.
CS can be more influential and impactful when it comes to customers achieving successful outcomes by harnessing more powerful customer insights, communication, onboarding, predictive analytics, education, and customer/community feedback.
What’s Next?
GenAI has a significant impact on customer experience. More to come in my next article - with a surprising prediction.
Post:
GenAI is an Opportunity and not a Threat. It is disruptive and here to change the role of Customer Success professionals.
In this article, I focus on the positive aspects of this change and the potential impact on future CS functions. I also refer to future predictions by Morgan Stanley and Gartner that all CSMs should consider as part of their professional development plan.
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