Assignment Insight: How AI Is Changing What Transformation Specialists Need to Offer

AI is becoming increasingly embedded within enterprise transformation programmes, influencing how organisations approach everything from ERP and data to cloud, supply chain and business process transformation.

For technology specialists, this is beginning to change the skills and experience organisations value.

Technical expertise remains essential. Organisations still need experienced SAP consultants, enterprise architects, data specialists, cloud engineers, programme leaders and other professionals who understand complex technology environments. However, as AI becomes part of the systems and processes these specialists work with, technical capability alone may no longer be enough to differentiate one candidate from another.

The opportunity is not necessarily to reposition yourself as an AI specialist. Instead, it is to understand how AI is affecting your existing area of expertise and demonstrate where your knowledge, judgement and experience can add value alongside it.

Here are four areas transformation specialists should consider.

1. Understand how AI is affecting your existing specialism

There is understandable pressure within the technology market to develop AI skills, but that does not mean every transformation professional needs to become an AI engineer.

A more useful starting point is understanding how AI is being applied within your existing discipline.

An SAP specialist might consider how AI is being incorporated into ERP processes and workflows. A supply chain consultant may need to understand its application within forecasting, planning and optimisation. A data professional will increasingly encounter questions around the quality, accessibility and governance of the information being used by AI systems.

This allows you to build on the expertise you already have rather than attempting to reposition yourself around an entirely new discipline.

When reviewing your experience, ask yourself:

• Where is AI beginning to influence the platforms or processes I work with?

• Which elements of my role could become more automated?

• Where will organisations continue to require specialist judgement or experience?

• What additional knowledge would complement my existing expertise?

The strongest positioning is likely to come from combining established specialist knowledge with an understanding of how your market is evolving.

2. Demonstrate where your judgement adds value

As technology becomes more capable, the value of experience does not disappear. In many transformation environments, it becomes more important.

Enterprise programmes involve decisions that cannot always be reduced to a technical output. Organisations have to balance competing priorities, manage stakeholders, understand legacy environments, assess risk and determine how technology should operate within complex business processes.

This is where experienced specialists can differentiate themselves.

Rather than presenting your experience purely as a list of technical responsibilities, demonstrate where your judgement influenced an outcome.

For example, instead of:

"Responsible for SAP S/4HANA data migration."

Consider:

"Led data migration activity across a multi-country SAP S/4HANA programme, working with business and technical stakeholders to resolve data-quality issues and reduce migration risk ahead of go-live."

The technology expertise is still clear, but so is the value of the individual behind it.

As AI becomes more widely used, examples of decision-making, problem-solving and specialist judgement will become increasingly useful when demonstrating what you can contribute to a programme.

3. Develop AI and data literacy around your core expertise

You do not necessarily need deep technical AI expertise, but having a working understanding of the technology is becoming increasingly valuable.

This includes understanding what AI can realistically do within an enterprise environment, where its limitations sit and what needs to be in place for organisations to use it effectively.

Data is particularly important.

AI initiatives depend heavily on the quality, structure, accessibility and governance of enterprise data. For professionals working across ERP, finance, supply chain, manufacturing and other enterprise systems, understanding this relationship can make existing experience more relevant to emerging transformation programmes.

Consider developing your knowledge around areas such as:

• AI functionality within the platforms you already work with

• enterprise data quality and governance

• security and regulatory considerations

• automation and process redesign

• how AI implementation affects existing workflows and operating models

The objective is not to collect AI terminology for your CV. It is to understand enough to have credible conversations about how the technology affects your area of expertise.

4. Position yourself around the problems you can solve

One of the most effective ways to strengthen your profile is to move beyond describing what you know and explain what your expertise enables an organisation to achieve.

This becomes particularly important as roles evolve.

A hiring manager may receive several profiles containing similar platforms, certifications and technical keywords. The candidates who are easier to assess are often those who provide context around where that expertise has been applied and the problems it helped solve.

Think about the challenges behind your previous assignments.

Were you brought into a programme because a migration was falling behind schedule?

Did an organisation need specialist expertise that was missing internally?

Were you responsible for stabilising a platform following implementation?

Did you help improve a process, resolve an integration problem or prepare a programme for go-live?

These details provide considerably more information about the value you can bring to the next organisation.

As AI changes some of the tasks performed within transformation teams, being able to articulate this value will become increasingly important.

Final Thought

AI will continue to influence the structure of enterprise transformation teams, but technology specialists should be careful not to assume that remaining relevant means abandoning their existing expertise and becoming AI specialists.

Deep knowledge of enterprise platforms, processes and programme environments remains valuable. What is changing is the context in which that expertise is being applied.

The specialists best positioned for the next phase of the market will be those who understand how AI is affecting their discipline, continue developing relevant knowledge and can clearly demonstrate the judgement, experience and problem-solving capability they bring to complex transformation programmes.

At Digisourced, we work with technology professionals and organisations delivering transformation programmes across Europe. If you're considering your next contract or permanent opportunity, or would like to discuss how demand for your specialist skills is evolving, get in touch with our team.