C-Suite Perspectives On AI: Craig Crisler Of SupportNinja On Where to Use AI and Where to Rely Only on Humans

An Interview With Kieran Powell

Data Analysis and Validation: AI-powered tools can easily handle large datasets — and the insights that lie within — to drive significant insights into CX, sentiment, and financial data. That kind of cross-sectional data is hard and labor-intensive for non-AI-supported groups.

Aartificial intelligence (AI) continues to advance and integrate into various aspects of business, decision-makers at the highest levels face the complex task of determining where AI can be most effectively utilized and where the human touch remains irreplaceable. This series seeks to explore the nuanced decisions made by C-Suite executives regarding the implementation of AI in their operations. As part of this series, we had the pleasure of interviewing Craig Crisler.

With 20+ years of experience in operational excellence and modern people management, Craig’s “be the grease, not the glue” philosophy has proven that the best outcomes happen when we let go of the obsession with efficiency and invest in value-centric relationships instead.

His personal journey in overcoming addiction has transformed how he shows up as a proud parent, loving husband, and trusted business leader. Now that Craig has implemented an empathy-informed mindset, his perspectives may be considered idealistic or unconventional at times, but he can guarantee you they are always rooted in reality, gratitude, and connection.

Thank you so much for your time! I know that you are a very busy person. Our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?

I think my business career started with a failed attempt at rock stardom. I was playing in bands in and around the Bay Area of California. I took a small inheritance and produced a band with a simple contract, starting a record company at 16 years old. From there, it grew with two more bands and led to my first taste of scaling something to exit at the age of 18. From there, my career spans multiple start-ups ranging from military tech products to educational technology with four successful exits among scaling 12 startups in my career.

Let’s now shift to the central focus of our discussion. In your experience, what have been the most challenging aspects of integrating AI into your business operations, and how have you balanced these with the need to preserve human-centric roles?

Like with any new tech (and I’m old enough to remember a lot of it as a digital immigrant), I think the bridge to it being cool and new versus useful is always the hurdle to overcome. We must remember to apply a new tool or feature because it strategically adds value — not just because it’s cool, new AI.

For SupportNinja, this plays out directly with some of our clients who are jumping headfirst into the shallow end at times with AI, and then we are picking up the pieces as we move to follow a more formal process looking at the people, processes, and systems (with an overlay of CX strategy) to find AI solutions that fit best.

Can you share a specific instance where AI initially seemed like the optimal solution but ultimately proved less effective than human intervention? What did this experience teach you about the limitations of AI in your field?

It’s often easy to try to apply blanket solutions to all clients or all situations without realizing the power of aligning the AI enablement to the specific client’s strategic process. One example of this is a virtual SME for agents in the CX space, where they can ask the AI questions to get some real feedback on the best solutions to propose to the customer.

We initially thought that this would work well for ALL CX clients, since it’s a low-cost and potentially low lift. But we realized that a blanket approach wouldn’t apply to more complex tech CX support, which is nuanced and customized by the end users we support.

To emphasize the point, a high-end luxury brand approached us saying it wanted to implement an AI chatbot to improve speed to resolution for customer issues. The problem? With an average price point of $20,000 per purchase, the customer for this brand demands a high-touch customer experience driven by collaboration and product customization. Knowing the brand’s voice, we instead recommended RPA and other AI tools that give human agents access to more information at their fingertips, leading to improved response time and improved First Call Resolution, which supports their brand voice.

How do you navigate the ethical implications of implementing AI in your company, especially concerning potential job displacement and ensuring ethical AI usage?

I fundamentally disagree with the prevalent notion that AI will drive job loss in our industry and beyond. Where are jobs being lost based on AI? Not due to implementation to optimize workforces. It’s a loss of jobs due to companies having to cut costs to pay for expensive AI implementation and research currently.

We fundamentally believe that the future of work (Outsourcing 2.0) will involve high-powered, smaller, and tech-enabled teams doing high-value work for clients.

Rather than driving job loss, it will allow companies to leverage technology to drive higher value human interactions to improve CX while enabling end users and CX professionals to make empowered decisions.

Could you describe a successful instance in your company where AI and human skills were synergistically combined to achieve a result that neither could have accomplished alone?

There are too many instances to name, but I will point out how we see this playing out with multiple clients. In a world where AI becomes embedded in the CX process, the days of traditional BPO metrics are gone. Average Handle Time and Hold Time, although effective in measuring productivity, don’t necessarily reinforce a robust CX strategy. We’ll see a rise in the new paradigm of measures like First Call Resolution, where we measure whether customers are able to resolve their issues on the first touch with the CX team.

We see this across clients where numerous AI tools (from RPA to API integration to sentiment analysis) are feeding CX agents information in real time while they resolve a customer’s issue. AI empowerment via this kind of data density gives the CX professional meaningful and actionable data they can use to customize their response to resolve issues and support their customers. This super-powered agent amplifies their humanity and empathy on an interaction with more information to ensure the customer is satisfied.

Looking towards the future, in which areas of your business do you foresee AI making the most significant impact, and conversely, in which areas do you believe a human touch will remain indispensable?

AI — and how it can aggregate and draw insights from large amounts of often disparate data — will transform how CX professionals interact with and draw from numerous CX interactions across time. I imagine a world where we can benchmark CX work across industries and companies to improve CX performance and the resulting customer experience. In addition, this will drive CX agents to amplify and improve upon their empathy and connect better with the customers in a meaningful way. This is where I think AI will make us all more human.

This is where a human touch will become indispensable. AI cannot hug (and please let’s not talk about huggin’ robots). But most CX interactions are driven by some form of frustration or problem. With AI handling the minutiae in the back end, the agent can focus on having a better sense of empathy, informed by social, cultural, and geographical factors — which invites their humanity into the interaction. At times, we’re just humans working together, and this is where you’ll see humans becoming (I hope) more human as AI enters the picture.

You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. :-)

Outside of the real big ticket items… reduction of poverty and food scarcity, universal healthcare, etc., which are amazing and would likely have the most impact…

As AI becomes more embedded in our lives and we are fed more and more information based on what the tools think we want and need, I would love to see a rise in humanity as AI allows us to elevate what we all collectively do.

AI will enable us to take the mundane and repetitive aspects of our lives and free up time for us to elevate our thinking and what we do. This is where I would love to see us elevate our humanness in response to AI giving us more time. More empathy, more discussion, more diversity of thought, more inclusion, and more hugs.

How can our readers further follow your work online?

I post frequently on LinkedIn, as well as the SupportNinja blog.

It has been said that our mistakes can be our greatest teachers. Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lesson you learned from that?

I could, of course, list out my missteps early on in my career (forgetting to mention speaking to a room full of teachers about Edtech and saying our organization’s goal is “to touch your kids” and the cackles of laughter that followed). But mistakes happen always, and I am a human (even in the age of AI), so here is an example of a mistake I made last month:

I believe and trust strongly in the team that surrounds me; leaning heavily on promoting from within the ranks to leadership positions. I, unfortunately, placed a person in a position to fail. By placing the person in a position to challenge to grow and manage a part of our business, I missed the key signs that they were in over their heads. They may have had the heart, but not the experience or insight to scale with the position. Unfortunately, the lesson of “trust but verify” means the world when you are challenging folks to step up.

Are you working on any exciting new projects now? How do you think that will help people?

At SupportNinja, we have a theme every year. This year it is Shinka, roughly translated from Japanese to mean “evolution.” The idea of transforming our services and driving client value is at the core of this theme, and is emphasized in two of its five pillars: innovation is necessary and client value creation is our guide.

Our initiative around tech enablement for our clients emphasizes this. In traditional outsourcing models, technology enablement emphasizes contract value and benefits the client little, which goes against what we know the future of outsourcing to be: tech-enabled people solutions.

We don’t take a one-size-fits-all approach to tech enablement; instead we first understand the customer’s problem(s), then deploy and empower our people with the latest technology, allowing us to deliver true customer value (and provide career growth opportunities for our ninjas). This is unique in our space as it truly aligns the rapid advancements in technology (from AI to RPA/machine learning) to our clients’ strategic initiatives.

Based on your experience and success, what are the “5 Things To Keep in Mind When Deciding Where to Use AI and Where to Rely Only on Humans, and Why?” How have these 5 things impacted your work or your career? Please share a story or an example for each.

AI

1. Content Moderation (specifically in more potentially psychologically traumatizing situations): We all know the stories of how content moderation in community and social media platforms was built on the backs of low cost laborers overseas suffering the psychological impact of vetting through deplorable content to provide safety and protection to their end users. AI (specifically machine learning and CLM-based algorithms) can save humans the psychological trauma of reviewing inappropriate content and lessen the impact to humans in many cases.
2. Data Analysis and Validation: AI-powered tools can easily handle large datasets — and the insights that lie within — to drive significant insights into CX, sentiment, and financial data. That kind of cross-sectional data is hard and labor-intensive for non-AI-supported groups.

Human

1. When your brand requires human interaction: This is a constant conversation with our clients at SupportNinja. Someone could throw an AI chatbot at any CX interaction, but what is your brand voice? For example, for a high-end retailer with a highly personalized, high-touch brand position, an AI tool wouldn’t meet the customer’s demanding expectations of human interaction to drive satisfaction and brand loyalty. This also goes for highly customized tech solutions/products or SaaS solutions that require nuanced response to drive customer satisfaction.
2. When your customers need empathy and not preordained scripting (e.g. high- pressure or intense human interaction): Currently funeral homes are not utilizing AI tools in wide swaths, car accident claims adjusters are not being replaced by AI tools, and, although it is being tested, we aren’t seeing AI doctors sitting at your bedside asking you your pain level. These may seem like silly examples, but they do point to a definitive line between what is human and what is technology. There are points where, ultimately, human-to-human interaction is more relevant and meaningful based on situational and cultural requirements.

Better Together

1. Enabling interaction and heightening humanity: The future is tech enablement to heighten and empower human interaction in CX. For example, you can leverage AI sentiment analysis and customer data processing to empower a customer’s support interactions. Imagine a world where a Customer Experience agent (which is where AI is taking the traditional Customer Support agent) is fed information on sentiment (where the caller is tone-wise), what their problem is via data analytics (what the caller might need), and given solutions to resolve the problem via API and seamless RPA data integrations (how we solve the caller’s problem) — even before joining a customer call. This happens in a flash, and the agent picks up the call: “Hello, I’m so sorry you are having a problem with X; I have some solutions for you.” The agent then focuses not on gaining insight, getting information, and finding a solution, but on how to solve issues and improve the client experience, human to human.

This was very inspiring. Thank you so much for joining us!

About The Interviewer: Kieran Powell is the EVP of Channel V Media a New York City Public Relations agency with a global network of agency partners in over 30 countries. Kieran has advised more than 150 companies in the Technology, B2B, Retail and Financial sectors. Prior to taking over business operations at Channel V Media, Kieran held roles at Merrill Lynch, PwC and Ernst & Young. Get in touch with Kieran to discuss how marketing and public relations can be leveraged to achieve concrete business goals.