Posted on: Jan 23, 2026
Why Automation and AI Are No Longer an IT Topic
For many organizations, automation and AI initiatives still start with technology selection: platforms, vendors, architectures. Yet experience across Global Business Services (GBS), Shared Services Centers (SSC), and corporate functions shows a consistent pattern: technology itself is rarely the main constraint.
What differentiates organizations that scale automation successfully is not the sophistication of their tools, but the way they redesign processes, distribute ownership, and govern change. Automation has become an operating model question, not an IT one.
Automation Starts With Process People, Not With Tools
High-impact automation initiatives rarely originate in central IT. They start with people who understand how work actually happens across the end-to-end process.
The strongest results come from teams that combine:
- deep process knowledge,
- a technology-oriented mindset (not necessarily advanced coding skills), and
- the willingness to challenge existing ways of working.
When automation is driven by process experts close to operations, organizations avoid building solutions that look good technically but fail to change outcomes.
Automation Is a Process Redesign, Not Activity Replacement
One of the most common leadership mistakes is automating individual activities without changing the underlying process.
Real value is created when organizations:
- simplify processes,
- standardize them end-to-end,
- remove unnecessary controls and handoffs,
- only then apply automation technologies such as AI, RPA, or low-code tools.
This is not theory. Gartner’s research on hyperautomation highlights that organizations which automate fragmented or overly complex processes significantly reduce expected benefits and increase long-term maintenance effort (Gartner, Hyperautomation: A Strategic Roadmap, Gartner Research).
Business-Driven Automation Scales Faster
The most effective automation model today is business-driven automation.
In this model:
- operational functions such as Finance, HR, Procurement, or Customer Operations identify automation opportunities based on productivity, quality, and risk objectives,
- IT provides platforms, architecture standards, security frameworks, and integration capabilities.
IT acts as an enabler, not a gatekeeper. Ownership of outcomes stays with the business, which significantly increases accountability and adoption.
When Central IT Becomes a Scaling Constraint
In many large organizations, central IT unintentionally slows down automation initiatives.
Typical challenges include:
- long planning and approval cycles,
- high delivery and change costs,
- focus on large system implementations rather than incremental improvements,
- strong concerns around security and long-term maintenance.
Gartner has repeatedly pointed out that overly centralized automation governance limits speed and discourages innovation, especially in environments where business units are under strong productivity pressure (Gartner, Top Strategic Technology Trends and Hyperautomation research notes).
Low-Code and No-Code Are Changing How Automation Scales
Low-code and no-code platforms are fundamentally reshaping automation delivery models.
Organizations that initially relied on traditional development approaches increasingly move toward low-code solutions because they:
- bring solution building closer to the business,
- reduce dependency on scarce IT capacity,
- shorten time-to-value,
- enable faster experimentation and iteration.
According to Gartner’s Low-Code Application Platforms research, low-code is a key enabler for scaling automation beyond IT, particularly in GBS and SSC environments where speed and adaptability are critical (Gartner, Magic Quadrant for Enterprise Low-Code Application Platforms).
Automation Maintenance Does Not Have to Sit in IT
A frequent concern among leaders is long-term support and maintenance.
In practice, maintenance can be successfully owned by process teams when supported by:
- clear documentation standards,
- AI-generated technical and process documentation,
- defined ownership by process owners rather than central IT.
This model reduces bottlenecks, improves accountability, and keeps automation closely aligned with process evolution.
Scale Is Not a Justification to Block Innovation
Organizational scale should not be used as an argument to stop innovation.
Security, compliance, and data protection are non-negotiable—but they should be addressed through guardrails, not blanket restrictions. Leading organizations define:
- approved platforms and tools,
- clear access and data usage rules,
- lightweight governance for low-risk solutions.
This approach allows local teams to deliver high-ROI solutions without compromising enterprise standards.
Rethinking ROI: From Local to Enterprise Perspective
When automation ROI is evaluated only at a local level—GBS, SSC, or a single function—many high-impact initiatives never get funded.
Productivity, quality, and resilience benefits often materialize across multiple functions and geographies. Gartner emphasizes that hyperautomation programs should be evaluated from an enterprise perspective to avoid systematic underinvestment in productivity improvements (Gartner, Hyperautomation: Business-Driven Approach).
Structure Matters More Than Tools
How automation capabilities are organized has a direct impact on results.
Organizations that temporarily remove strong process experts from daily operations and give them a mandate to redesign processes end-to-end consistently deliver better outcomes. This structure enables holistic thinking instead of incremental task optimization.
Measuring Automation Maturity the Right Way
The most important question for leaders is not: How many bots or AI solutions do we have?
A better question is:
How capable is our organization of continuously simplifying processes and implementing change?
Automation maturity is reflected in:
- speed of change,
- confidence in deploying new solutions,
- collaboration between business and IT,
- ability to adapt processes without fear.
Five Key Takeaways for Leaders
- Automation and AI are governance challenges, not technology challenges. Ownership must sit close to business processes, with IT as an enabler.
- Without process change, there is no automation ROI. Simplification and standardization come first.
- Overly centralized IT models limit speed and scale. Long decision cycles delay high-ROI initiatives.
- ROI should be assessed at enterprise level. Local P&L logic leads to underinvestment in productivity.
- Capabilities and mindset outweigh tools. Sustainable advantage comes from the ability to change continuously.
Moving Forward
Automation and AI are no longer experimental topics. They define how organizations operate, improve, and scale.
Leaders who focus on governance, process excellence, and capability building—supported by the right technology—will be best positioned to turn AI into lasting business impact.
Author, based on “GBS Masters” discussion on Jan 14th, Warsaw: “Process Transformation and Automation (including AI)”:
Edyta Krzemińska
PR & Marketing Lead