In This Article:
Workplace Harmony: How Humans and AI can Work Together
We are moving from what machines can do for us to what machines can be for us. Machines are evolving from being our tools to becoming our teammates. Gartner predicts that by 2025, GenAI will be a workforce partner for 90% of companies worldwide. - Mary Mesaglio, Distinguished VP Analyst at Gartner
I recently hosted ITSM veteran and thought leader Roy Atkinson (CEO, Clifton Butterfield LLC) on a topic that’s a core part of our product philosophy at Atomicwork – Workplace harmony: How humans and AI can work together.
Roy covered it in great detail, starting with AI and its role in ITSM and concluding with concrete steps that organizations need to take to augment humans with the power of AI.
Here’s a summary of our discussion.
What are we dealing with in the first place?
For the uninitiated, the GenAI wave that we see all around us, say, in the form of ChatGPT or Claude, is, in fact, narrow AI. Narrow AI, though very powerful, is limited in what it can do.
It is trained on one narrow aspect, and it can potentially do that very well. In the days to come, this will certainly evolve and become more powerful.
So, when we consider AI in IT service management or customer-facing systems, we generally refer to narrow AI (or GenAI, a form of narrow AI).
Before we get into the specifics, it is important to understand the respective strengths of humans and AI.
Given each group's broad strengths, the smart thing for companies to do is combine them as one team which can result in faster and more efficient work, reduced costs, and higher profits.
With that said, let’s see what AI can do in ITSM.
1. Automation
There’s nothing so useless as doing efficiently that which shouldn’t be done at all. - Peter Drucker
IT receives a ton of mundane and repetitive requests, like password reset and access to apps. IT support agents have been trying to streamline or optimize these for ages. This takes away valuable time without really requiring the expertise of IT support agents.
Anyone working in IT should be relieved of these tasks. With AI, these can be automated, freeing IT people to work on high-value work.
2. Speed
One of AI's biggest benefits is speed. What if we could use it to accelerate common use cases?
Let’s consider ticket summaries.
Anyone who has managed an IT service desk knows that there’s no consistency in how different agents log ticket summaries. One agent might write long and meticulous reports while another one will say 'Changed some settings'.
Assuming that the average agent takes roughly three minutes to type a ticket summary and handles 20 tickets a day, that’s one whole hour of saved time per day (or 5 hours a week, on average).
Now, what can you do with all that saved time? Absolutely anything that’s more productive than summarizing ticket logs!
3. Quality assurance
As you already know, QA is a manual process that involves reviewing call recordings or transcripts at random and looking for issues.
But what if you could have a complete 5-point quality assessment on every single contact? Wouldn’t that be a game-changer?
Of course!
An AI-based QA assistant can tell you the top 5 things that end users are looking for so you can prioritize them—not just based on the ticket topic but also on what they mentioned on the call. How’s that for productivity?
To sum up, AI will take over the simple and often repetitive work so IT folks can focus on the more complex work that could move the needle for the company.
Just to clarify, the above are just a few illustrative examples. With creativity and tech advancement, you can implement all this and more.
Roy also shared an interesting data point: According to HDI’s State of Technical Support in 2023, only 31% of service desks provide 24/7 support.
This means these service desks aren’t supporting remote work, hybrid work, and distributed teams.
With AI, you can do this seamlessly.
McKinsey’s ‘State of AI in early 2024’ report aligns with this:
The average organization using GenAI is doing so in two functions, most often in marketing and sales and in product and service development — two functions in which previous research determined that GenAI adoption could generate the most value — as well as in IT.
Most commonly reported GenAI use cases within functions
The ‘State of AI in IT 2024’ report from Atomicwork and ITSM.tools found that the top anticipated benefits of AI in IT include enhanced data analytics (45%), self-service chatbots (38%), improved employee experiences (34%), and workflow automation (34%).
What are the future trends?
McKinsey research suggests that, because of the emergence of GenAI, about half of today’s business activities could be automated a decade earlier than previous estimates had projected. Keeping this in mind, here’s what could be next on the horizon for ITSM.
1. Generative AI
GenAI can be used to create knowledge articles and documentation, enabling both IT staff and end-users to find solutions more independently. This could significantly reduce the workload on IT support teams and empower users to solve issues independently.
2. AI-driven insights
Continuous improvement powered by AI analytics will help organizations refine their ITSM strategies and optimize workflows. AI can parse large amounts of data and identify patterns that might be hard for humans to detect.
3. Human-centered AI
The future of ITSM is predicted to involve a balanced approach that leverages both AI capabilities and human intelligence and emotion. While AI can handle many mundane tasks, human judgment and empathy remain crucial for optimal results.
As McKinsey’s puts it: “Employees and managers should have a clear understanding of GenAI’s strengths and weaknesses and how the use of the technology is linked to the organization’s strategic objectives. Given the technology’s potential to accelerate automation, senior leaders could counter employees’ prevailing fears of “replacement and loss” with messaging about GenAI’s potential for “augmentation and improvement” — and its ability to significantly enhance the employee experience.”
Challenges and considerations while using AI
Like most major changes, the AI-human harmony comes with its share of challenges and the need for an action plan.
- Data quality and integration: The effectiveness of AI depends on the quality of data and integration with ITSM systems.
- Ethical and privacy concerns: We must address ethical issues and ensure data privacy and security.
- Job displacement and upskilling: It is necessary to ensure that the workforce is constantly upskilled to handle emerging roles.
According to our ‘State of AI in IT 2024’ report, the top three areas where our respondents felt that AI shouldn’t be used were:
• Ethical and legal decision-making (41%)
• People management (30%)
• Customer relationship management (29%)
How should companies run a job impact analysis?
Roy proposes a structured approach for companies to assess how changes due to AI might affect various job roles.
- Scope identification: Defining the boundaries of the analysis, including which jobs, departments, or processes will be examined.
- Stakeholder analysis: Identifying all parties who might be affected by these changes.
- Impact evaluation: Assessing the potential effects of these changes on individuals, workflows, and the overall organization.
- Readiness assessment: Evaluating how prepared the organization and its employees are for the impending changes.
- Communication requirements: Planning how to effectively communicate the changes and their impacts to all relevant parties.
- Resource and training requirements: Identifying what new resources or training might be necessary to support these changes.
- Risk assessment: Analyzing potential risks associated with the changes and developing necessary mitigation strategies.
- Data collection and analysis: Gathering and examining relevant data to inform decision-making.
- Reporting and action planning: Summarizing findings and developing concrete plans to implement changes and manage their impacts.
- Follow-up and monitoring: Continuously tracking the effects of changes and making adjustments as needed.
A good chunk of these need to be done before beginning the change process. It is, therefore, important for leaders to carefully consider and weigh their actions before implementing them.
What skills can your IT team consider to stay relevant?
Roy has a few areas that your team can focus on to become valuable resources for their organizations.
1. Data management and governance
This involves organizing, storing, and protecting data effectively. As AI systems rely heavily on data, understanding how to properly manage and govern data is crucial. This includes ensuring data quality, implementing security measures, and complying with regulations.
2. Knowledge management
This focuses on effectively capturing, organizing, and sharing information within an organization. In the AI era, the ability to manage and leverage collective knowledge becomes even more critical as it forms the basis for training AI systems and making informed decisions.
3. Prompt engineering
This is a relatively new skill specific to working with AI language models. It involves crafting effective inputs or ‘prompts’ to get the desired outputs from AI systems. Mastering this skill allows professionals to better utilize AI tools and extract more valuable information from them.
4. AI ethics and policy
As AI becomes more prevalent, understanding the ethical implications and helping shape policies around AI use is increasingly important. This includes considerations of bias, privacy, transparency, and the societal impact of AI technologies.
These skills complement, rather than replace, existing expertise, allowing professionals to adapt and thrive.
In conclusion
The integration of AI in ITSM is rapidly evolving, with current applications primarily focused on narrow AI.
AI demonstrates significant potential for handling low-level ITSM tasks efficiently, offering both immediate and long-term benefits when used to augment human capabilities. However, as organizations embrace AI, it's crucial to address potential biases and carefully consider ethical implications.
The synergy between AI and human expertise promises to revolutionize ITSM practices, making it imperative for businesses to start planning for this collaborative future now. By thoughtfully implementing AI solutions alongside human talent, organizations can optimize their ITSM processes and stay ahead in an increasingly digital landscape.
As Mary Mesaglio, of Gartner, says, “It is important to note that everyday AI will go from dazzling to ordinary with outrageous speed. Everyone will have access to the same tools, and it will not provide a sustainable competitive advantage. Everyday AI is the new table stakes.”
Table stakes.
Organizations need to start working towards harmony between human and artificial intelligence.
