2030: The Future of Enterprise Service Delivery – Part 1 

Top global industry research houses and consultancies tell us the world around us is changing rapidly and at an increasing pace, putting businesses into VUCA (Vulnerable, Uncertain, Complex, Ambiguous) situations.  

Assuming this trend continues, along with AI hype turning into widespread global adoption and no major technological setbacks in the next 5 years, what could the Enterprise Service Delivery look like in 2030? 

Source: statista.com

Over the next 5 years, a few key ingredients will play a part in shaping the future of Enterprise Service Delivery: 

• Service Purpose: Service departments (incl. IT) attempting to fulfil their purpose (supporting the business in enabling maximum employee productivity with as little frustration as possible) 
• Debt: Removal of inefficient, archaic processes and outdated technology where possible 
• New Tech: Incorporation of new technologies, best practices, and approaches 
• Cultural change: Driving behavioural shift towards efficiency and experiential gains 

However, to receive the funds required for the above, service departments will need to continuously prove how any of the projects satisfy business demand to support the delivery of broader business objectives: 

As an employee in 2030, what will you need to do well? Arguably, this may not differ too much from the current workforce requirements, and you will most likely want to:  

• Feel equipped to do your job 

• Feel like you are contributing, making a difference 

• Have opportunities to learn new things and grow your careers 

• Feel like you will be cared for when the need arises (e.g. illness or childbirth) 

• Feel like you belong, that the company’s purpose, values, and that actions align with yours 

With the above assumptions in mind, let’s get to it! 

AI image created by Microsoft Copilot prompt: “create an image of a futuristic office space in central London with agents sitting around their computer desks.” 

Hyperautomation 

Service Purpose:  

With hiring freezes becoming commonplace across the globe, it is no wonder CIOs are turning to Hyperautomation; looking at problem-solving from a technology perspective first before “throwing people at it”, as they have historically done.  

In turn, “forty-three per cent of CIOs are automating business and IT processes, 32% are implementing AI applications, and 29% are making data more available as part of their business-centric charter” (CIO.com, 2024).  

This trend will only continue to grow, and by 2030, Hyperautomation will be the standard approach to solving business problems, including identifying ways to increase the productivity of the end-user audience in the Enterprise Service Departments. 

Debt:  

Current project management approaches will become the biggest cultural and process debt in adopting Hyperautomation. Relevant best practice updates and training will be required to extract ROI from modern Project and Product Management platform implementations.

Image source: Microsoft Copilot - Prompt: “Create a graphic for Hyperautomation” 

New Tech: 

Rapid technological advancements are why 93% of UK businesses say there is an IT Skills gap (Forbes, 2023). This talent shortage is reflected in rising day rates and businesses outdoing one another in the working benefits they offer.  

By 2030, technology will help close the gap, introducing self-implementation and AI-driven automated enterprise-wide integration and workflow building as a standard in business platform set-up and optimisation. Professional services specialist workers in the Oracle, SAP, ServiceNow, or Salesforce ecosystems must shift their focus and skills from manual workflow building and platform administration to more strategic architecture and roadmap advisory.  

Cultural change:  

With an increase of Gen-Z workers and only a small percentage of baby boomers left on active duty by 2030, Gen X will become the leading voice of “if it’s not broken, don’t fix it.”  

However, with AI mapping out and monitoring process flows, continuously suggesting improvements and calculating relevant ROI if implemented, there will be little space for arguing against change. The trust in the results produced by AI will increase significantly, helping to determine business cases and support them with relevant data, such as expected ROI. 

Fully personalised Service Delivery 

Service Purpose: 

Retail technology companies have been “spoiling” their direct customers with quick and easy access to their services, up-to-date service/product catalogues with user reviews, fast delivery, easy returns, and new, useful features daily. In 2024, this starkly contrasts with employees’ service experience in most workplaces. You can read more about it in my article. By 2030, we must reduce this experiential delta to deliver on our promise of enabling productivity.  

Debt: 

Current SLA-based models for measuring the Service Delivery quality must be rehauled to remove the Watermelon Effect. A human-centric approach will enable mapping out the experience journey from the end-user perspective and prioritising end-user experience improvements. 

One of the biggest challenges that global organisations and MSPs, in particular, face is multilingual support. Finding people with the right skills in the country where you are looking to provide support or in your global support centre is very challenging and costly.  

New Tech: 

Connecting work devices and tracking technologies to the monitoring platforms will move most data gathering into the background, such as application loading times, workflow delays, or availability. AI will become a standard way of processing the data and suggesting improvements, with some of them being automatically developed and pushed into QA.  

Fully automated provision of work devices will be an expected standard by employees, from NLU-powered self-service ordering to delivery and set-up. Background systems (e.g. CMDB, AD allocation, applications, security, experience) will be automatically updated and continually monitored with near-zero agent touch.  

Data from body-tracking devices will start entering the workspace. The data will monitor overall health, including stress levels, and AI will automatically suggest immediate actions, topics for the next 1-2-1 review, or a discussion with work wellbeing specialist teams. Extending the duty of care that employers can provide to further improve and enhance productivity. 

Simultaneous immediate language translators will enable service delivery to be done in any language, with the appropriate voice intonation, whilst processing what the end user is saying and looking for possible solutions and knowledge in real time. This service will not be free but several times cheaper than hiring a multi-lingual resource. Also, it will enable agents with great skills but only speaking one language to progress in their careers.  

Cultural change: 

Personal health data use in the workplace will require tight data security, handling, and governance. It must deliver true benefits to the end-users, such as stress level management, before they feel comfortable with their employer’s surveillance.  

Service Agents’ roles will move from manual, repetitive, tedious tasks and data entry (e.g. auto-generated voice call summaries, emails, and suggested improvements) to focus on more personalised service delivery and proactive problem-solving. Data from their own devices will then enable them to learn to handle complex, stressful situations better. 

However, agents will require new skills related to their ability to use different AI-powered features, and support organisations should start preparing them for the journey now, in 2024. 

Spatial Computing 

Service Purpose: 

The communication channels have seen very few significant updates in the last few decades. By 2030, Spatial Computing will enter the workplace, enabling improved remote collaboration and service delivery and more personalised interaction with a human touch on the go. We are already seeing spatial audio make its way into collaboration tooling, but this will get enhanced as the technology and market evolves. 

Debt: 

Moving from desktop PCs and face-to-face service delivery in the workplace to “anywhere-anytime” models and working from home support has posed many challenges for service delivery teams. These will continue over the next five years as a balancing act between BYOD, zero-trust security, employee device choice, and automation of procurement, operational, and service delivery workflows.  

New Tech: 

Having the privilege of testing the Vision Pro at Apple’s Experience Centre inside the Battersea Power Station enabled me to envision the level of personalisation and effective communication this channel can bring, including emotion projection and ticket resolution collaboration. Indeed, Spatial Computing is at the stage of the first Macintosh computer or first-generation iPhone, but the technology is finally reaching business usability levels. By 2030, I expect Spatial Computing to be one of the channels required to be supported by Service Delivery departments - Necrobotics less so.  

Cultural Change: 

End User: “My laptop keeps getting a blue screen each time it boots up.” 

NLP Chatbot: “Let me connect you with one of our agents. In the meantime, please put on your Spatial Computing headset.” 

Agent: “Thank you for joining me today. From what you have described, this may be related to a global technology incident. We must reboot your machine to Safe Mode and erase a file. Are you happy for me to walk you through it with our screens side by side?” 

Spatial Computing will enable the agents to collaborate with the end users in the same space, providing previously unreachable levels of empathy and service quality in remote sessions, making end users feel cared for and supported, enabling a higher level of self service. 

Summary

In this part, we have talked about VUCA (Volatility, Uncertainty, Complexity, Ambiguity), AI hype, and four key elements of each prediction – Service Purpose, Debt, New Technology, and Cultural Change – applied across first three predictions – Hyperautomation, Fully Personalised Delivery, and Spatial Computing. 

In Part Two, we will explore Data Control and Protection, Experiential Learning, and Employee Benefits.