EX - Service Management Consulting and Training: Tedder Consulting

Why are AI assistants given human-like names?

Apple provides Siri[i]. Amazon has Alexa[ii]. Samsung features Bixby[iii]. And there are literally dozens of other examples, in use both publicly and privately.

The attribution of human characteristics to non-human entities is known as anthropomorphism. Attributing human intent to non-human entities, such as pets, robots, or other entities, is one way that people make sense of the behaviors and events that they encounter. We as humans are a social species with a brain that evolved to quickly process social information.[iv]

There are numerous examples of anthropomorphism with which we are familiar, and honestly, don’t even think twice about. In Toy Story[v], the toys can talk. In Animal Farm[vi], the animals overthrow their masters and govern themselves. In Winnie-the-Pooh[vii], Christopher Robbin interacts with Winnie, a talking bear.

Is this why AI-enabled chatbots and digital assistants are given human-like names? To make us want to talk to them? To make it easy to interact with them? To influence our thinking and behaviors?

Without over psycho-analyzing the situation (and I am far from qualified to do so), the answer to the above questions is “yes”.

The good – and not so good – of today’s AI capabilities

AI capabilities have been around for quite some time. While philosophers and mathematicians began laying the groundwork for understanding human thought long ago[viii] , the advent of computers in the 1940s provided the technology needed to power AI. The Turing Test, introduced in 1950, provided a method for measuring a machine’s ability to exhibit behavior that is human-like. The term and field of “artificial intelligence”, coined by John McCarthy in 1956, soon followed.

The past few years have seen a dramatic expansion of AI capabilities, from machine learning to natural language processing to generative AI. That expansion has resulted in impactful and valuable capabilities for humans. AI is well-suited for managing tedious and repetitive tasks. AI can be used to initiate automated actions based on the detection of pre-defined conditions. AI can facilitate continual learning across an organization based on the data captured from interactions with and use of technology. And most recently, AI is developing a growing capability to respond to more complex queries and generating responses and prompts to aid humans in decision-making.

But despite all the progress with AI, there are some things that are not so good. Miscommunication can occur due to limitations of a chatbot or an AI assistant in understanding user intent or context. A simple example is the number of ways we as humans describe a “computer”, including “PC”, “laptop”, “monitor”, or “desktop” must be explicitly defined for an AI model to recognize the equivalence. AI is not able to exhibit empathy or the human touch, resulting in frustration, because humans feel that they are not being heard or understood.[ix] AI is not able to handle complex situations or queries that require nuanced understanding; as a result, AI may provide a generic or irrelevant response.[x] The quality of responses from AI is directly dependent upon the quality of the input data being used – and many organizations lack both the quality and quantity of data required by AI to provide the level of functionality expected by humans. Lastly, but perhaps most importantly, the expanding use and adoption of AI within organizations has resulted in fear and anxiety among employees regarding job loss.

Techniques that will help humanize AI

Several techniques can help organizations better design human interactions with AI. Here are a few to consider that can help humanize AI.

Employing design thinking techniques – Design thinking is an approach for designing solutions with the user in mind. A design thinking technique for understanding human experience is the use of prototypes, or early models of solutions, to evaluate a concept or process. Involving the people that will be interacting with AI through prototypes can identify any likes or encountered friction in the use of AI technology.
Mapping the customer journeys that (will) interact with AI – A customer journey map is a visual representation of a customer’s processes, needs, and perceptions throughout their interactions and relationship with an organization. It helps an organization understand the steps that customers take – both seen and unseen – when they interact with a business.[xi] Using customer journey maps helps with developing the needed empathy with the customer’s experience by identify points of frustration and delight.
Thinking in terms of the experience – What is the experience that end-users need to have when interacting with AI? Starting AI adoption from this perspective provides the overarching direction for making the experience of interacting with AI more “human”.

Start here to make AI use more human

AI adoption presents exciting opportunities for increasing productivity and improving decision-making. But with any technology adoptions, there is the risk of providing humans with suboptimal experiences with AI. Here are three suggestions for enabling good human experiences with the use of AI.

Define AI strategy – Success with AI begins with a well-defined strategy that identifies how AI will enable achievement of business goals and objectives. But AI success is not just business success or technical success with AI models, but also whether users are happy with AI and perceive it to be a valid solution. [xii]
Map current customer journeys – Mapping current customer journeys may expose where user interactions are problematic and may benefit from the introduction of AI.
Start and continually monitor the experience – Happy Signals, an experience management platform for IT, states that “humans are the best sensors”. Humans are working in technological environments that are in a constant state of change and evolution. Actively seeking out and acting upon feedback from humans regarding their experiences with technology raises awareness of the user experience and fosters a more human-centric approach to technology use and adoption.

The best way to ensure that AI-enabled technologies are more human is to design them with empathy. Design thinking, customer journey mapping, and experience management will help ensure that AI stays in touch with the “human” side.

Need help with customer journey mapping? Perhaps using design thinking techniques to develop solution-rich, human centered solutions for addressing challenges with customer and employee experience? We can help – contact Tedder Consulting for more information.

[i] “Siri” is a trademark of Apple, Inc.

[ii] “Alexa” is a trademark of Amazon.com, Inc. or its affiliates.

[iii] “Bixby” is a trademark of Samsung Electronics Co., Ltd.

[iv] https://www.psychologytoday.com/us/basics/anthropomorphism , retrieved March 2024.

[v] Lasseter, John. Toy Story. Buena Vista Pictures, 1995.

[vi] Orwell, George. Animal Farm. Collins Classics, 2021.

[vii] Milne, A.A., 1882-1956. Winnie-the-Pooh. E.P. Dutton & Co., 1926.

[viii] Wikipedia. “History of artificial intelligence”. Retrieved March 2024.

[ix] https://www.contactfusion.co.uk/the-challenges-of-using-ai-chatbots-problems-and-solutions-explored , retrieved March 2024.

[x] Ibid.

[xi] https://www.qualtrics.com/experience-management/customer/customer-journey-mapping , retrieved March 2024.

[xii] Ganesan, Kavita. “The Business Case for AI: A Leader’s Guide to AI Strategies, Best Practices, & Real-World Applications”. Opinosis Analytics Publishing, 2022.

It may be hard to believe, but the term “experience economy” is nothing new. The term was first mentioned in this 1998 Harvard Business Review article. In the article, the authors posited that an experience occurs when a company intentionally uses services as the stage, and goods as props, to engage individual customers in a way that creates a memorable event. In other words, it’s not enough to have great products and services; it’s the experience of the customer that differentiates companies from their competition.

Fast forward to today, and these “memorable events” have become a significant factor in today’s employee-employer relationship, broadly known as employee experience (EX). Companies providing a good EX can attract and retain top talent, deliver better experiences to their customers, and have employees who are more committed to the company.

What is the experience like when employees are interacting with technologies and services within your company? Is your organization actively measuring and improving those experiences? Is your company committed to a great employee experience?

These are answers that an XLA, or Experience Level Agreement, will reveal.

XLAs provide a different perspective

In IT, there is a tendency to focus on and measure things like technology performance and process execution. Often there is little attention given to how end users perceive the quality and effectiveness of technologies, apart from when an end user reports an incident or makes a service request.

An XLA provides a different perspective. An XLA provides focus to end-users’ experience and needs, by measuring the outcomes and the value of services provided. An XLA seeks to understand how end users feel about their interactions with technology and with those with whom they interact during those interactions.

By understanding the experience, organizations can identify where measures reported by IT do not reflect the end user experience. Understanding the experience also helps identify potential areas for improvement, whether that be with a service, a product, a process, or any other aspect that the end user leverages to get their jobs done.

XLAs are becoming increasingly popular as employers realize that good EX is essential for business success. ” This article from reworked.co discusses the impact of a positive EX:

23% higher profitability
28% reduction in theft
81% reduction in absenteeism
41% reduction in quality defects
64% reduction in safety incidents

Clearly, good EX is good business.

XLA vs. SLA

So, what’s the difference between an XLA and an SLA, or Service Level Agreement?

An XLA focuses on happiness and productivity metrics from the end-user perspective.[i] XLAs focuses on measuring the quality of the user experience, rather than just technical metrics like uptime or response times.

An SLA is an artifact of many ITSM (IT Service Management) adoptions. An SLA, as described by ITIL^®[ii], is a documented agreement between a service provider (typically IT) and a customer that identifies both services required and the expected level of service.[iii] SLAs are intended to manage expectations and ensure both IT and non-IT parts of the organization understand their responsibilities. SLAs should also provide a framework for measuring performance and holding the provider (IT) accountable if they fail to meet their commitments.

SLAs are managed by the service level management practice, which is typically found within IT departments. The purpose of service level management is to set clear, business-based targets for service levels, and ensure that delivery of services is properly assessed, monitored, and managed against these targets. [iv] The SLAs produced should relate to defined business outcomes and not simply operational metrics.

An XLA is not meant to replace an SLA but work alongside SLAs to ensure a holistic view of value and results from the use of IT services.

But wait, isn’t quantifying, reviewing, and discussing business value and results part of SLAs and service level management?

Well, yes. But most organizations that claim to have SLAs, really don’t have SLAs.

The problem with most SLAs

What many companies are calling “SLAs” fall far short of being a service level agreement. Why?

Services are not defined and agreed. What and how IT services enable or facilitate business results and business value have not been defined and agreed between IT and non-IT senior managers. Furthering the confusion, what many IT organizations call a “service catalog” only describes technologies and service actions that consumers can request, not business value and outcomes.
The so-called “SLA” discusses IT, not the organization. SLAs discuss IT operational performance – typically related to only the service desk – and not business performance. Indeed, many of the issues related to SLAs (for example, the Watermelon Effect) are as a direct result of ITSM tools using the term “service level agreement” as a misnomer for business performance target
IT arbitrarily decides its own performance and success metrics. And these metrics are either measures that an ITSM platform administrator used in her last job, or metrics pre-configured within the ITSM platform, or metrics that a senior IT leader picked. Regardless, these performance measures are usually not relevant to anyone in the organization outside of IT.
Organizations (including both IT and non-IT leaders) take the wrong approach to SLA. Neither service providers (IT) nor service customers (non-IT managers) invest the time and effort to define services, the relationship and expectations between IT and the non-IT parts of the organization, and agree on business-relevant terms and performance measures. As a result, there is no shared, mutual understanding established regarding the use and importance of technology within the organization.

Close the gaps between SLA and XLA

Understanding how technologies and processes enable business outcomes, as well as what the organization – and the employee – truly value, is critical for a good EX within today’s organizations.

If XLA adoption reveals EX challenges, closing the gaps between SLAs and XLAs will help. Here are some things to try.

Define services – in business, not IT terms. Clearly defining and agreeing IT services between IT and non-IT leaders, including service-specific performance measures. Mutual understanding of business value and outcomes from the use of services is foundational for good EX.
Apply Design Thinking. Design thinking is a human-focused method of problem-solving that prioritizes the solution instead of the problem. Identify where EX is falling short, then apply design thinking techniques to redesign the experience to meet both the employee’s and employer’s needs.
Are your SLAs really SLAs? If SLAs aren’t documented or agreed with non-IT leaders, or SLAs do not identify clear, business-based measures for quantifying success, then you don’t have SLAs. Treat this as an opportunity to build good business relationships and establish true SLAs, resulting in better business outcomes and EX.

While XLA adoption can be a real revelation for an organization, it is not a magic wand for instantly improving EX. Like SLAs, XLAs can only be effective through collaboration, leadership, and having a continual improvement mindset across the entire organization. Resolving the gaps between SLAs and XLAs will help.

[i] https://www.happysignals.com/the-practical-guide-to-experience-level-agreements-xlas

[ii] ITIL is a registered trademark of AXELOS Limited.

[iii] ITIL Foundation: ITIL 4 Edition. Norwich: TSO (2019)

[iv] Ibid.

Tag Archives: EX

The more AI we become, the more human we need to be