Rethinking how work gets done
AI TRANSFORMATION SERVICES
Helping organisations move from fragmented AI adoption to a structured transformation programme across AI strategy, workflow redesign, operating models, capability, governance, agents, automation and implementation.
Transform how your organisation works with AI
AI transformation is about more than introducing ChatGPT, Microsoft Copilot, Gemini or Claude. It means rethinking how work gets done, which workflows should change, where automation can create value and how AI should be governed and scaled.
SMK helps organisations move from fragmented AI adoption to a structured transformation programme across AI strategy, workflow redesign, operating models, capability, governance, agents, automation and implementation.
Whether you are starting to formalise AI adoption or already experimenting extensively, SMK can help determine what needs to change next.
What does AI transformation actually mean?
Most organisations already use AI somewhere.
Staff may be using ChatGPT or Microsoft Copilot. Marketing teams may be working with Gemini, Claude, Canva AI or Adobe Firefly. Leaders may have introduced AI policies. Individual teams may already be experimenting with agents and automation.
But individual tools and isolated experiments do not necessarily amount to transformation.
AI transformation begins when organisations start asking bigger questions:
Where can AI create measurable business value?
Which workflows should be redesigned?
What should people stop doing manually?
Where should AI assist, automate or augment work?
How will existing roles change?
What new skills will teams need?
Which AI platforms, agents and automations should be deployed?
How should AI use be governed?
How will adoption and performance be measured?
Could AI change the products, services or experiences we offer?
Where should an organisation start with AI transformation?
A useful starting point is not:
Which AI tool should we buy?
A better question is:
What would we like AI to materially change within our organisation over the next 12 to 36 months?
That shift moves the conversation away from licences and features and towards business outcomes.
From there, SMK can assess the current state, identify priority opportunities and build a practical roadmap for implementation.
For one organisation, the priority may be redesigning high-volume workflows.
For another, it may be establishing clearer AI governance and improving adoption of Microsoft Copilot or ChatGPT.
A marketing, advertising or communications agency may need to rethink delivery models, production capacity, client service and new AI-enabled offerings.
A government organisation may prioritise approved workflows, responsible use and stronger accountability.
The right AI transformation strategy depends on the organisation, its operating environment and the outcomes it wants to achieve.
What is the difference between AI adoption and AI transformation?
There is an important difference between giving people AI tools and transforming how an organisation works.
An organisation might already have:
- Microsoft Copilot licences
- ChatGPT accounts
- An AI policy
- Staff training
- Teams experimenting with agents
- AI workflows
- AI features enabled inside existing platforms
All of those can be valuable.
Transformation happens when these activities start connecting.
AI strategy informs investment.
Priority workflows are redesigned.
Roles and responsibilities evolve.
Technology is matched to genuine business needs.
Governance enables responsible adoption.
Capability becomes more consistent across teams.
Leadership can see where AI is creating value.
The objective is not simply more AI use. It is a better-performing organisation enabled by AI.
What can AI transformation deliver?
A successful AI transformation programme should create measurable improvements in how work gets done.
Greater productivity and capacity
Reduce repetitive work, accelerate analysis and execution, and enable teams to deliver more without increasing resources at the same rate.
Faster, better workflows
Redesign inefficient processes around AI, automation and agents rather than layering new tools onto old ways of working.
Stronger AI adoption and capability
Move from scattered experimentation towards consistent, role-specific use supported by practical skills and clear expectations.
Clearer operating models
Define how responsibilities, decision-making and workflows change as people increasingly work alongside AI systems and agents.
Safer, more practical AI governance
Give employees clarity on approved tools, data, review, accountability and responsible use.
Measurable business impact and growth
Track productivity, quality, capacity and customer outcomes while identifying where AI can create new services, customer experiences or commercial opportunities.
What can an AI transformation programme include?
Every organisation is different, so AI transformation should not begin with a predetermined technology stack or generic maturity model.
SMK programmes can draw from eight connected areas.
1. AI Strategy & Roadmap
Establish where AI can create meaningful value and what the organisation should prioritise.
SMK can support AI transformation strategies, opportunity prioritisation, leadership workshops, business cases, investment priorities, one to three-year roadmaps and measures of success.
The core question is:
What should AI materially deliver for the organisation over the next few years?
3. Workflow Redesign & Automation
Some of the biggest AI opportunities sit inside everyday business processes.
SMK can identify, prioritise and redesign workflows across areas including:
– Marketing & Communications
– Research
– Content development & Social media
– Campaign management
– Reporting & Analytics
– CX, Sales & Recruitment
– Stakeholder engagement
– Knowledge management
– Internal communications
– Administration
A workflow transformation programme may assess dozens of activities before selecting the highest-value opportunities for deeper redesign.
AI, automation and agents can then be introduced where they materially improve speed, quality, capacity or decision-making.
5. AI Platforms, Agents & Automation
Strategy needs to translate into practical execution.
Depending on the organisation, SMK can support work with ChatGPT, Microsoft Copilot, Gemini, Claude and specialist AI applications.
This can include:
– Platform selection and adoption
– Custom GPTs and AI assistants
– AI agents
– Workflow automation
– Knowledge-enabled AI
– Prompt and instruction libraries
– Reusable workflow systems
– Integration with existing business tools
Where deeper systems engineering or infrastructure is required, SMK can work alongside internal technology teams or specialist implementation partners.
7. AI Adoption & Change Management
AI transformation ultimately depends on whether people change how they work.
SMK can support leadership engagement, internal communication, AI champions, practical working sessions, coaching, communities of practice and adoption measurement.
The focus moves from measuring access to measuring value.
2. AI Operating Model
AI can change how teams are structured, how decisions are made and how work moves between people, platforms and functions.
SMK can help organisations explore:
– AI responsibilities and ownership
– Centralised versus distributed AI capability
– Human and AI responsibilities
– Future team structures
– Decision-making and approval models
– Specialist AI roles
– Centres of excellence
– Internal AI support models
The goal is to create an operating model that reflects how work changes as AI becomes embedded across the organisation.
4. AI Capability & Workforce Enablement
As workflows change, people need to know how their roles and responsibilities change with them.
SMK helps organisations determine:
– Which activities can be accelerated or automated
– Where human judgement remains critical
– Which skills become more important
– How different roles should use AI
– What leaders need to understand
– Where capability gaps exist
Transformation programmes can then include practical training, coaching, working sessions and role-specific enablement built around real organisational workflows.
6. AI Governance & Responsible AI
Organisations need to move quickly without creating unnecessary risk.
SMK can help establish practical AI governance covering:
– AI policies
– Approved tools and usage guidelines
– Data and privacy considerations
– Human review requirements
– Approval processes
– Brand and content controls
– Risk classification
– Tool evaluation
– Governance responsibilities
– Responsible AI principles
Good governance should help organisations adopt AI safely and confidently, not simply create more restrictions.
8. AI-Enabled Products, Services & Growth
For some organisations, AI transformation goes beyond internal productivity.
AI can change what the organisation offers customers or clients.
SMK can help identify opportunities around AI-enabled services, new customer experiences, managed offerings, proprietary workflows, intellectual property and new commercial models.
For marketing, advertising, digital and communications agencies, as well as consultancies and professional services organisations, AI can reshape both the economics of existing work and the services clients will buy in future.
How does SMK approach AI transformation?
SMK moves from diagnosis and prioritisation through to workflow redesign, capability building, implementation and measurement.
DISCOVER
Understand current AI use, capability, technology, workflows, governance and organisational readiness.
DEFINE
Establish AI transformation objectives, priorities, strategy and roadmap.
REDESIGN
Rethink priority workflows, operating models, roles and responsibilities.
ENABLE
Build the skills and organisational capability required to work differently.
IMPLEMENT
Introduce practical AI tools, workflows, agents, automations and supporting systems.
EMBED
Strengthen adoption, governance, leadership and repeatable working practices.
MEASURE
Assess whether AI is improving productivity, quality, capacity, service, performance or commercial outcomes.
A 40-person marketing, advertising or communications agency does not necessarily need to become a 60-person agency to deliver significantly more work.
That is one of the more consequential possibilities created by AI.
Consider an integrated agency delivering strategy, creative, content, media, performance marketing and client services.
Staff are already using ChatGPT, Claude, Gemini and AI features inside creative, media and marketing platforms.
Individual teams are getting value from AI, but adoption is inconsistent.
Some people are considerably more advanced than others.
Client expectations are changing rapidly.
Management can see the opportunity but does not yet have a coordinated plan.
The transformation challenge
AI could potentially affect almost every part of the agency.
Strategy and research
Research, audience insight, competitor analysis, briefing and strategic development can all be accelerated.
Creative, content and production
AI changes ideation, copywriting, image generation, video production, versioning, adaptation and personalisation.
Media and performance
AI is becoming embedded across Google, Meta, TikTok, LinkedIn and other advertising platforms, changing planning, optimisation, creative testing and reporting.
Account management and client service
Account teams increasingly need to understand AI well enough to advise clients, identify opportunities, scope new work and challenge poor assumptions.
Operations and delivery
Reporting, administration, project management, resourcing, knowledge sharing and internal production processes can all be redesigned.
Commercial model and new services
Clients are beginning to buy AI-related services that barely existed a few years ago, while also expecting existing agency services to become faster, smarter and more efficient.
How could SMK support the agency?
An agency AI transformation programme might include:
- Assessing current AI use, capability and opportunities across the agency.
- Developing an agency-wide AI strategy and transformation roadmap.
- Identifying and prioritising workflows across strategy, creative, media, account management and operations.
- Redesigning priority workflows around AI, automation and agents.
- Establishing an AI operating model.
- Building specialist capability across agency disciplines.
- Developing reusable prompts, agents, workflows and internal AI systems.
- Creating AI governance and quality-control frameworks.
- Helping leaders determine where productivity and capacity gains should be reinvested.
- Identifying new AI-enabled services the agency could take to market.
What could the result look like?
The agency does not simply become quicker at producing the same work.
It can become a different kind of agency.
A 40-person business may be able to deliver substantially more work without adding headcount at the same rate.
Strategists can spend less time gathering information and more time interpreting it.
Creative teams can explore and test more ideas.
Account teams become better equipped to advise clients about AI.
Production and delivery become more efficient.
Capacity gains can be reinvested into better work, stronger client service or growth.
New AI-enabled services can create additional revenue opportunities.
AI changes how the agency operates, what it delivers and what it can sell.
That is AI transformation.
For government, the opportunity is not simply faster content production.
It is the ability to reduce repetitive knowledge work while maintaining the governance, privacy, accessibility, accountability and human oversight expected of public organisations.
Consider a government department with a large communications, engagement or corporate affairs function.
Microsoft Copilot may already be available.
Some staff are experimenting with generative AI.
Others remain unsure about what they are allowed to use.
Leadership wants productivity improvements but must also consider privacy, governance, accessibility, record keeping and public accountability.
The transformation challenge
The objective is not simply to make staff use AI more often.
The department needs to determine where AI can safely improve how work gets done.
Potential areas might include:
Communications planning
Supporting research, stakeholder analysis, planning and briefing.
Content development
Accelerating first drafts, adapting material for different audiences and channels, summarising complex information and supporting accessibility.
Stakeholder engagement
Helping teams analyse feedback, identify themes and prepare engagement materials.
Research and intelligence
Synthesising large volumes of information and supporting environmental scanning.
Reporting
Reducing manual reporting and accelerating the movement from data to insight.
Knowledge management
Making approved organisational knowledge easier for staff to find and use.
Administration
Reducing repetitive internal work and improving document preparation.
How could SMK support the department?
A government AI transformation programme might include:
- Assessing current AI use, readiness, capability and risk.
- Establishing clear AI transformation objectives and priorities.
- Mapping high-volume and high-value workflows.
- Identifying workflows suitable for AI assistance, automation or redesign.
- Developing practical AI governance and usage frameworks.
- Establishing clear human review and accountability requirements.
- Designing role-specific AI workflows.
- Developing reusable Copilot, ChatGPT or other approved AI solutions.
- Training teams against their actual work rather than generic AI examples.
- Establishing adoption and performance measures.
- Supporting leaders as AI capabilities and organisational practices continue to evolve.
What could the result look like?
Staff spend less time on repetitive drafting, summarising, research and administration.
Teams have clearer processes for responsible AI use.
Good practices become standardised rather than sitting with a handful of advanced users.
Leaders gain greater visibility over adoption and value.
People have more capacity for higher-value work requiring judgement, stakeholder understanding and subject-matter expertise.
AI becomes part of how the department operates rather than a separate technology initiative.
For not-for-profits and NGOs, AI can create capacity in organisations where resources are already stretched and teams are expected to deliver across fundraising, communications, stakeholder engagement, research, service delivery and reporting.
The opportunity is not simply to produce more content.
It is to reduce repetitive work so specialist teams can spend more time on mission-critical activity.
A transformation programme might identify opportunities across donor communications, grant research, stakeholder analysis, reporting, knowledge management, campaign development and administration.
At the same time, the organisation may need clear controls around privacy, sensitive data, beneficiary information, accuracy and human review.
SMK could help prioritise appropriate workflows, establish responsible-use frameworks, redesign high-value processes and build capability around approved AI platforms.
The result can be greater organisational capacity without compromising the judgement, trust and accountability the organisation depends on.
AI can help limited resources go further while keeping people focused on the work where human expertise and relationships matter most.
No.
AI transformation does not need to mean a huge multi-year technology programme.
For many organisations, the most effective approach is progressive.
Start by understanding the current state.
Identify where the biggest opportunities exist.
Prioritise the workflows, teams or functions where change will create the greatest value.
Implement.
Measure.
Learn.
Expand.
A programme might initially focus on Marketing, Communications or another priority function before expanding more broadly.
Another organisation might begin with ten high-value workflows.
A marketing or communications agency might prioritise client delivery, production efficiency, capacity and new services.
A government or not-for-profit organisation might begin with governance, capability and approved workflows.
The aim is to create evidence and momentum before scaling transformation more widely.
Most organisations do not need to begin by committing to a large transformation programme.
A focused AI Transformation Diagnostic can establish where you are today, where AI can create the greatest practical value and what should happen first.
The diagnostic may include:
- Leadership interviews
- AI adoption and capability assessment
- Workflow mapping
- AI opportunity identification
- Technology and platform review
- Governance review
- Risk and readiness assessment
- Opportunity prioritisation
The output is a practical AI Transformation Roadmap covering:
- The highest-value opportunities
- Priority workflows and teams
- Required AI platforms, agents or automation
- Capability and workforce requirements
- Governance and risk controls
- What should happen now, next and later
- How progress and value will be measured
For some organisations, this becomes the first phase of a broader SMK transformation programme.
For others, it provides the clarity required for internal teams or implementation partners to proceed.
No.
Training may be an important part of transformation, but it addresses a different need.
AI Transformation
For organisations that want to change how a team, function or organisation operates.
AI Training & Capability
For organisations that need to build AI knowledge, skills and confidence.
AI Strategy & Advisory
For organisations that need expert advice, prioritisation or an AI roadmap.
AI Auditing & Benchmarking
For organisations that need to understand current AI adoption, capability, gaps, risks and opportunities.
AI Solutions & Enablement
For organisations that need practical AI agents, assistants, workflows, automations or systems configured and implemented.
AI Coaching & Support
For leaders and teams that need ongoing expertise while implementing and evolving their approach.
A broader AI transformation programme may combine several of these services.
Individual services address specific needs. AI transformation changes how the organisation works.
SMK supports AI transformation across organisations and business functions where AI has the potential to materially change workflows, productivity, capability and service delivery.
Our strongest areas of experience include:
- Marketing
- Communications
- Corporate Affairs
- Marketing, advertising, digital and communications agencies
- Customer experience
- Professional services
- Government departments and councils
- Not-for-profits and NGOs
SMK can also support broader cross-functional transformation where AI affects research, sales, knowledge management, People functions and other areas of organisational work.
Engagements can range from transforming one function through to broader organisation-wide programmes.
AI transformation sits between strategy, technology and people.
Technology-led programmes can deploy platforms without materially changing how people work.
Training programmes can improve capability without redesigning the workflows around it.
Strategy programmes can produce ambitious roadmaps that struggle to translate into everyday execution.
SMK works across all three.
For more than 15 years, SMK has helped organisations build practical capability across marketing, communications, digital and other business functions. More than 100,000 professionals have been upskilled through SMK since 2010.
SMK specialises in the organisational side of AI transformation: strategy, workflows, operating models, capability, governance and adoption, with practical AI implementation where it supports the work.
Our transformation programmes can connect:
- AI strategy and roadmap
- Workflow redesign and automation
- AI operating models
- ChatGPT, Microsoft Copilot, Gemini, Claude and specialist platforms
- AI agents and practical solutions
- Workforce capability
- AI governance and responsible use
- Adoption and change management
- Measurement and performance
Where deeper systems engineering, security or infrastructure work is required, SMK can work alongside internal IT teams, technology partners or specialist AI implementation firms.
The focus is on whether AI materially improves how the organisation works.
AI transformation engagements are tailored to the organisation, the scale of the opportunity and the level of support required.
They can range from:
AI Transformation Diagnostic
Assess the current state, identify priority opportunities and establish a practical roadmap.
Functional AI Transformation
Redesign a defined function or portfolio of workflows across strategy, capability, governance and implementation.
Broader AI Transformation Programme
Coordinate multiple workstreams across teams, workflows and organisational priorities over a longer transformation programme.
Engagements are scoped on a project basis following an initial discovery conversation.
Frequently asked questions about AI Transformation
An AI transformation strategy defines how an organisation will use AI to improve workflows, operating models, capability, customer outcomes and business performance.
It should identify priority opportunities, required technology, governance, capability requirements, implementation priorities and measurable outcomes.
Start with the business change you want AI to create rather than the platform you want to deploy.
SMK can assess the current state, identify high-value AI opportunities and determine which workflows, teams or capabilities should be prioritised first.
No.
Technology decisions should be informed by business needs, workflows, data considerations and existing systems.
Platform selection can form part of the engagement where required.
Yes.
Existing environments such as Microsoft Copilot, ChatGPT, Gemini or Claude can be incorporated into the transformation programme alongside other approved tools.
It can.
Agents and automation can form part of an AI transformation programme where they improve a priority workflow or business process.
The starting point is the workflow and business case, not the technology itself.
No.
Automation is one possible outcome.
AI can also improve research, analysis, decision support, communication, creativity, knowledge access, customer experience and service delivery.
The objective is to redesign work intelligently rather than automate everything that can technically be automated.
Priority should reflect business value, frequency, effort, feasibility, risk and the potential improvement in productivity, quality or capacity.
This helps organisations focus investment where meaningful outcomes are most achievable.
Governance should be designed alongside AI adoption and workflow change rather than added afterwards.
Policies, data considerations, human review, approval requirements, tool selection and accountability should evolve together.
Yes.
For many organisations, transforming one function or portfolio of high-value workflows is the most practical starting point before expanding more broadly.
Yes.
SMK can work alongside internal technology and transformation teams or external implementation partners.
Our role can focus on AI strategy, workflows, operating models, capability, governance, adoption and practical use, while specialist technical teams manage deeper infrastructure or engineering requirements.
Measures should reflect what the organisation is trying to achieve.
Depending on the programme, these might include time saved, capacity created, workflow adoption, quality improvements, reduced cycle times, employee capability, customer outcomes or commercial performance.
Licence activation alone is not a meaningful measure of transformation.
Where could AI create the greatest change in your organisation?
You may already have Microsoft Copilot licences, teams using ChatGPT, an AI policy and dozens of individual experiments.
The next challenge is deciding what those capabilities should materially change.
Which workflows should be redesigned? Where could productivity and capacity improve? Which roles will evolve? Where could agents or automation create value? What governance needs to be in place? How will you know whether the investment is working?
SMK can help turn those questions into a practical AI transformation strategy, roadmap and implementation programme.
Whether you want to transform one function, redesign priority workflows or develop a broader organisation-wide approach, the first step is understanding where AI can create the greatest business value.
Book a Discovery Call
If your organisation wants stronger AI adoption, clearer workflows or practical, cross-platform enablement, SMK can help.
Book a short conversation to explore scope, options and next steps.