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The impact of AI on implementation engineer skills

Discover the skills every implementation engineer should learn now to be successful in the future

Within the last 12 months, the world has seen artificial intelligence (AI) advance by leaps and bounds—in terms of both capability and availability. As AI becomes ubiquitous, implementation engineers are positioned to play a crucial role in managing and optimizing the adoption of this emerging technology. As such, the demand for professionals in this space is projected to grow significantly, with approximately 65,000 new implementation engineers added to the workforce by 2027.

However, this shift will also create disruption for implementation engineers and other technology-based jobs. To remain competitive in this new world of AI-driven processes, implementation engineers must adapt by developing the skills necessary to effectively leverage the increased technological capabilities. 

ServiceNow, in partnership with Pearson, recently completed a comprehensive study of how AI and other emergent intelligent technologies are expected to change the business landscape within the next five years. The results paint a positive picture for eight key roles within IT, including the role of implementation engineer. Despite the emergence of powerful AI and automation, workers in these roles will remain relevant—provided that they can evolve alongside new intelligent tools and develop the skills to use them effectively. 

Today’s implementation engineers are responsible for ensuring the successful implementation and integration of new systems and technologies into an organization's existing infrastructure. To do this, they depend on a broad range of technical expertise alongside soft skills necessary to effectively collaborate with cross-functional teams, project managers, business analysts, and developers. Implementation engineers typically also have a deep understanding of software development processes and best practices and work to ensure that new solutions align with the organization's strategic goals and requirements. 

Implementation engineers are instrumental in the successful adoption of new technologies, making them extremely valuable in today's job market. In fact, the current average annual salary for an implementation engineer in the United States is approximately $113,000.

The skills needed to find success as an implementation engineer include:

  • A technical background and expertise in software development processes and best practices

  • Problem-solving skills and the ability to troubleshoot issues (for addressing potential issues during implementation and testing)

  • Proficiency in project management and the ability to orchestrate multiple projects simultaneously

  • Communication skills (for collaborating effectively with cross-functional teams)

  • Adaptability (for working in fast-paced, fluid environments)

  • Attention to detail (to ensure that systems are optimized for performance and scalability)

  • A broad understanding of organizations' strategic goals and requirements (for aligning new solutions to established objectives)

  • Knowledge of emerging technologies (to drive innovation and improve efficiency)

  • The ability to train and educate end users on new technologies and systems

  • Documentation skills (for proper tracking and effective knowledge transfer to support teams)

Over the next five years, the expansion of AI will have noticeable effects on the roles and responsibilities of implementation engineers. With the increasing prevalence of automation and intelligent technologies, implementation engineers will need to adapt and develop new skills, including becoming proficient in leveraging AI capabilities to support and optimize their work. However, this also means that as AI becomes ingrained in more routine and low-level tasks, implementation engineers will have the capacity to focus on higher-level activities—such as strategy development and project management—to add value to their organizations.

And this number increases to 17% when including tasks that will be at least partially augmented by AI. As a result, this is expected to save implementation engineers up to 4.2 hours per week, which can be allocated to more strategic initiatives. 

The four technologies that will primarily drive this change are:

Process automation: Code programmed to complete predefined logical and rule-based processing tasks

Solution discovery: Agents using reinforcement learning (RL) and sensors to digest and solve unstructured, complex problems 

Predictive analysis: Tools that reactively use machine learning (ML) to conduct narrow analysis and make related predictions

The ServiceNow/Pearson report suggests that within the next five years, 4.8% of implementation engineer tasks will be automated

Sensory perception: Systems that use ML and sensors to detect and extract meaning from external stimuli

In addition, the study analyzed 15 implementation engineer tasks that are likely to experience transformation due to AI and automation. Among these tasks, three were identified as the most likely to be affected:

1. Documenting and communicating database schemas using accepted notations

2. Collaborating with system architects, software architects, design analysts, and others to understand business and industry requirements

3. Developing load-balancing processes to eliminate downtime for backup processes

With AI playing an increasingly important role in IT tasks and capabilities, implementation engineers must adapt and evolve their skill sets to remain competitive in the job market. Industry leaders must establish learning and development programs that will guide this talent transformation through upskilling and reskilling opportunities.

Out of 32 capabilities deemed critical for future positions, the top five areas in which implementation engineers will need to be highly proficient by 2027 are:

1. Retaining and improving foundational IT skills

2. Expanding critical thinking capabilities

3. Collaborating effectively across digital media

4. Engaging in ongoing learning

5. Focusing on maintaining and improving digital communication

With the evolution of AI technologies in business processes, tools, and roles, implementation engineers will continue to play a crucial role in organizations worldwide. However, they will not be immune to the effects of these changes.

Over the next five years, implementation engineers will need to acquire the necessary skills to utilize AI capabilities in enhancing and streamlining their tasks. Additionally, business leaders should identify proficiency gaps so that they can implement suitable training and upskilling programs to empower their engineers to succeed alongside AI, automation, and the emergent technologies that will shape the near future.

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