Contact center training and coaching methods and tools are undergoing both a technological transformation and a rethink of how best to help leadership and staff feel well trained and skilled in helping customers, according to consultant and Advisory Board member Laura Sikorski.
Contact centers are seeing a shift of repetitive skills from agents to AI and to having a hybrid mix of remote and in-office workers, she says. Leaders then need to be more comfortable with AI and with managing higher-skilled agents coming to work and enjoying speaking with customers regardless of their physical location.
These are important observations and recommendations. So, we decided to virtually chat with Laura to further explore these developments and others.
Q. What trends that you have seen emerge in the past 12 months do you expect to continue and change in the next 12 months?
My research has indicated the following trends for 2025 that will continue through 2026:
Training
- Taking place online and in the classroom at the same time.
- Personalized online training using AI-driven learning experiences.
- Wellness (stress management) and wellbeing foci.
- Helping leaders manage virtual teams and employees.
- Social and collaborative learning.
Coaching
- AI integration for real-time accountability and insights.
- In-person and virtual coaching will be more common.
- Emphasis on building communities and addressing social issues.
- Executive leadership coaching will be tied to performance indicators.
- Quality assurance (QA) techniques that assist staff with upskilling, reskilling, and right-skilling for their future.
Q. Let’s dive deeper into AI. Is it changing how agents interact with customers? If so, how? Is it different than past transformative applications e.g., ivr, speech recognition, crm software?
First, let’s get “back-to-basics” and see if we can figure out why AI has become the “hot” button for almost everything in the last two years.
Max Tegmark, president of the Future of Life Institute, has the following AI description: “Everything we love about civilization is a product of intelligence, so amplifying our human intelligence with artificial intelligence has the potential of helping civilization flourish like never before – as long as we manage to keep the technology beneficial.”
My interpretation of this description is to think of AI as the capability of technology to help a company better understand what their customers need to have for a pleasant experience and what staff need to make that happen. AI needs to be real-time so that appropriate departments can react accordingly.
“AI requires quality responses, training on the right or wrong results, process transcription with controls, and a strong execution strategy...” —Laura Sikorski
In my opinion, ChatGPT started it all by open sourcing information and responding back to inquiries with natural responses. It really empowered machine learning.
The next step was natural language linking responses to work processes i.e. Generative (Conversational) AI. It can create new content and ideas, such as text, images, audio, and video, based on the input it receives.
Generative AI differs from traditional AI, which is often focused on prediction or analysis, by its algorithms learning to recognize patterns in voice and data and then use them to generate new, original content.
Next comes Agentic AI, which empowers and analyzes the processes and maps out the structure to deliver answers.
Agentic AI refers to a type of AI that can act autonomously, make decisions, and take actions to achieve specific goals with limited human supervision. It’s like a virtual assistant that can think, reason, and adapt to changing circumstances without needing constant direction.
Previous IVR, speech recognition, contact center-as-a-service (CCaaS), and CRM software, in my opinion, were not robust enough to handle machine learning integration and screen pop requirements for a seamless transition.
Q. How can AI in the contact center be successful?
I believe that AI/machine learning, with complete prompt instructions, clearly defines outcomes/results that relate to customer relationships. It relies heavily on systems, including legacy systems, to handle all customer interactions.
But AI will only be successful IF customers and staff are asked how they feel about what human interaction is needed versus self-service.
By example, if the AI answers a call type and sees the customer is just not getting their question answered it should ask them if they would like to be transferred to a “live” agent. On the reverse, if the live agent has satisfied the customer, the agent can transfer the customer back to AI self-service if appropriate.
AI requires quality responses, training on the right or wrong results, process transcription with controls, and a strong execution strategy on what may need to be done differently in order for customers and staff to accept this technology.
Rollout of AI is expensive, and proof of concept is recommended. Test, retest, and test again to a small demographic to see if what you think is correct will indeed benefit your customers and staff.
Q. What are the benefits but also the challenges in having agents “partner” with AI applications when engaging with customers? But are agents skilled/educated enough to be taught how to use it proficiently? Is this a new skillset that they need to be assessed when hiring?
AI should: - Help agents not replace them.
- Coach while the agents are on interactions.
- Let chatbots handle the basic self-service interactions.
- Handoff to agents when the interactions get too complex.
- Track performance KPIs that result in developing skills not numbers.
- Reflect human responses.
- Always tell the truth.
I do feel AI implementation will change who and/or how you hire. The value of a skilled specialist will emerge to handle your customers with proper empathy and emotion.
Voice and data governance of AI responses is paramount for customer privacy adherence, especially if incorrect answers are given that could result in legal actions.
AI may encourage downsizing in the future and may increase attrition. But remember, you can automate tasks, but you still need people to build relationships.
Q. Let’s look deeper into AI as a coaching and training tool. Is it, and if so, how is it changing how agents are trained and coached? Could you discuss “train the trainer” on AI?
It appears that AI systems are rolling out faster than trainers can train the staff.
Do your trainers understand how AI works? Are they thoroughly versed in the skills that are needed to work with AI and any decision-making processes that will improve customer relationships?
Trainers must be included during the development and testing stages of AI as it will be their responsibility to empower the staff to use this new technology and feel comfortable with what it does.
The prompt development stage is critical to AI success. It might be technically correct yet would leave the customer frustrated and the agent caught in the middle.
We all know the importance of agent continuous training and we may need continuous AI empathetic learning for the future acceptance of AI.
Q. What are your recommendations to contact centers to help them coach and train their agents to their maximum and loyal potential?
Training and coaching is a two-way street. AI is constantly learning, therefore, so should continuous training and coaching programs.
Technology is rapidly changing, and staff need to feel comfortable in having an active role in enhancing how they are trained and coached. Issues that come up during live interactions should have a “Drop Box” type of approach for agents to leave comments, including areas of frustration that are occurring with AI.
“Do your trainers understand how AI works? Are they thoroughly versed in the skills that are needed to work with AI...?”
Team task force time should be scheduled weekly. It is important for agent staff to have input in how to make their interaction a more pleasant experience for them and your customers.
(I want to thank Bill Magnuson, CEO, CAIO and Founder of NexusBlue and Melissa Swartz, Founder of Swartz Consulting for their expert advice and counsel regarding AI implementation.)