Turn AI into better ways of working
Identify where AI can improve everyday work, redesign high-value workflows, equip teams to work effectively with AI, and build practical human-AI collaboration into the organization.
8 steps
5 steps
Illustrative example. Never a guarantee of productivity gains.
Adding AI to an old workflow doesn't automatically make it better
Organizations often introduce AI tools without changing the way work actually happens. Real AI productivity comes from redesigning how work gets done — not from layering a new tool onto an unchanged process.
More tools, but no better workflow
Duplicated effort across teams
Inconsistent outputs and quality problems
Employees using AI differently, unevenly
Excessive manual review erasing time saved
Unclear responsibility and unmanaged sensitive information
What we do
Global AI Charter helps organizations identify, redesign and improve workflows where AI can provide meaningful assistance. The goal isn't to automate everything — it's to determine what AI should do, what humans should do, and how they should work together.
The executive questions
Where is time being lost?
Identify repetitive, administrative and knowledge-intensive work.
Where can AI help?
Find tasks where AI assistance may improve speed, consistency, research, drafting or information processing.
What should remain human?
Identify decisions, approvals and activities requiring human judgment.
How should the workflow change?
Redesign the process around effective human-AI collaboration.
How do we know it works?
Define practical measures for quality, adoption, efficiency and risk.
Workflow discovery
We examine workflows across relevant organizational functions.
Knowledge work
- Research
- Writing
- Summarization
- Document analysis
- Information retrieval
- Internal knowledge management
Marketing
- Research
- Content development
- Campaign support
- Audience analysis
- Reporting
Sales
- Lead research
- Proposal support
- Account research
- CRM assistance
- Sales documentation
Customer operations
- Customer inquiry handling
- Response drafting
- Knowledge retrieval
- Case summarization
- Support workflows
HR
- Job description drafting
- Recruitment support
- Learning content
- Internal knowledge
- Administrative workflows
Finance
- Reporting support
- Document processing
- Reconciliation assistance
- Analysis
- Management reporting
Operations
- Process documentation
- Administrative tasks
- Data processing
- Quality checks
- Workflow coordination
Technology
- Software development assistance
- Documentation
- Testing support
- Technical research
- IT knowledge workflows
Workflow assessment
Each selected workflow can be examined through its current process, steps, inputs, outputs, decision points, repetitive activities, manual effort, bottlenecks, error points, information dependencies, data sensitivity, existing tools, human approvals, AI opportunities and risk points.
Workflow Opportunity Map
Number of steps, inputs and outputs
Decision points and human approvals
Bottlenecks and error points
Data sensitivity and existing tools
AI opportunity types
AI can support work in different ways.
Assist
AI helps a person complete a task.
- Drafting
- Summarization
- Research
- Brainstorming
- Analysis
Augment
AI expands human capability.
- Decision support
- Knowledge synthesis
- Pattern identification
- Complex research assistance
Automate
AI performs defined tasks within controlled boundaries.
- Classification
- Routing
- Repetitive document processing
- Structured information extraction
Coordinate
AI supports multi-step workflows.
- Information gathering
- Task sequencing
- Workflow orchestration
- Agent-assisted processes
Automation or agentic workflows should only be recommended where the process, controls, data and accountability requirements are appropriate.
Human-AI workflow design
Not every task should be automated. We help determine the appropriate human role.
Human-led
AI provides assistance, but humans perform the substantive work.
AI-assisted
AI completes defined portions of the workflow with human review.
Human-approved
AI generates an output or recommendation that requires human approval before action.
Human-supervised
AI performs a broader workflow under defined monitoring and escalation mechanisms.
Controlled automation
AI performs defined tasks within explicit boundaries, permissions and monitoring.
The appropriate model depends on the task, risk, consequences and organizational context.
Workflow redesign
For priority workflows, we design a future-state process. The objective is not simply to reduce steps — it's a workflow that is more effective, easier to manage, appropriately controlled, measurable and scalable.
Before
Collect → Read → Analyze → Draft → Review → Approve → Send
After
AI-Assisted Collection → AI Analysis → Human Review → Approval → Send
AI workflow templates
Depending on the engagement, we may develop reusable workflow patterns. These are templates, not automatic recommendations — each must be adapted to organizational requirements.
Research workflow
Question → Search → Collect → Analyze → Verify → Synthesize
Document workflow
Upload → Extract → Classify → Summarize → Review → Approve
Content workflow
Brief → Research → Draft → Review → Verify → Publish
Customer support workflow
Inquiry → Retrieve Knowledge → Draft Response → Human Review → Respond → Log
Management reporting
Collect → Analyze → Summarize → Validate → Present
AI tool & workflow assessment
We can assess how existing AI tools are being used across the organization — platforms, productivity tools, department-specific and unofficial tools, duplicated tools, workflow integrations, access practices and data handling.
This can reveal unnecessary duplication and workflow opportunities.
AI productivity framework
Our approach considers productivity across five dimensions. Productivity should never be evaluated using time savings alone.
Time
Can AI reduce unnecessary manual effort?
Quality
Can AI support consistency or improve access to information?
Capacity
Can employees spend more time on higher-value work?
Experience
Can AI make workflows easier for employees or customers?
Control
Can the workflow maintain appropriate verification, oversight and accountability?
Verification & quality
AI-generated output requires appropriate verification. Controls may include source checking, fact verification, human review, structured validation, quality checklists, approval requirements, exception handling and audit records.
AI can accelerate work. It does not remove the need for judgment.
Workflow risk assessment
Each workflow should be considered in context. Higher-impact workflows should receive stronger controls and human oversight.
Inaccurate or hallucinated outputs
Sensitive data exposure or privacy concerns
Security issues
Inappropriate automation
Insufficient human oversight
Unclear accountability
Vendor dependency
Workflow failure
Workforce integration
Workflow transformation only works when people can use the redesigned process effectively. Depending on scope, we provide role-specific AI guidance, workflow training, prompt and instruction patterns, verification practices, responsible AI guidance, workflow playbooks and internal adoption support.
AI Workforce Enablement →Role-specific AI guidance
Workflow playbooks
Prompt & instruction patterns
Internal adoption support
Productivity measurement
We help organizations define practical measures for transformed workflows. Do not present hypothetical productivity improvements as guaranteed outcomes.
Efficiency
- Processing time
- Turnaround time
- Manual steps
Quality
- Error rates
- Review findings
- Output consistency
Adoption
- Workflow usage
- Employee participation
- Repeat usage
Capacity
- Time redirected to higher-value work
- Workload distribution
Risk
- Exceptions
- Incidents
- Escalation frequency
- Control adherence
What you receive
Core deliverables- Workflow Assessment
- Workflow Opportunity Map
- AI Use-Case Map
- Current-State Workflow Analysis
- Future-State Workflow Designs
- Human-AI Role Definition
- Workflow Prioritization
- AI Tool Usage Review
- Verification & Quality Framework
- Workflow Risk Considerations
- Productivity Measurement Framework
- Implementation Recommendations
- Workflow playbooks
- Role-specific guidance
- Prompt / instruction templates
- Pilot design
- AI workflow prototypes / specifications
- Team workshops
- Adoption support
- Measurement dashboard design
Our process
Discover
Understand the organization's work, functions and strategic priorities.
Map
Document current workflows and identify friction.
Identify
Find practical AI opportunities.
Prioritize
Evaluate value, feasibility, risk and readiness.
Redesign
Create future-state human-AI workflows.
Enable
Prepare people to work with the redesigned workflows.
Measure
Define how effectiveness, quality, adoption and risk will be evaluated.
Who is this for?
Leadership
Functional teams
Organizations
When you need this
- Employees already use AI but workflows haven't changed
- Leadership wants measurable AI productivity improvements
- Teams spend significant time on repetitive knowledge work
- AI tools are being used inconsistently
- Multiple departments have duplicated AI tools
- You've identified use cases but need workflow design
- AI adoption is creating new quality or control problems
- You want to move from experimentation to practical implementation
When you should start elsewhere
Need to understand your overall AI position? Start with AI Readiness & Opportunity Assessment.
Need organization-wide strategic direction? Start with AI Strategy & Transformation Roadmap.
Primary concern is governance, risk or controls? Start with AI Governance & Responsible Adoption.
Main requirement is employee capability? Start with AI Workforce Enablement.
Pricing
Workflow Discovery
Focused review of selected workflows and AI opportunities.
AI Productivity Assessment
Structured assessment of productivity opportunities across selected functions.
Workflow Transformation Engagement
Detailed analysis and redesign of priority workflows with human-AI collaboration and measurement recommendations.
Multi-Function Transformation
For organizations requiring multiple departments, multiple workflows, workshops and broader transformation planning.
Enterprise
Depends on number of workflows, departments, organizational size, stakeholder involvement, transformation depth, workshops and technical requirements.
What's included
- Workflow discovery
- Current-state mapping
- AI opportunity identification
- Use-case prioritization
- Future-state workflow design
- Human-AI role definition
- Verification recommendations
- Risk considerations
- Measurement framework
- Implementation recommendations
What's not included
- Software development
- Production deployment
- Custom AI model development
- Full systems integration
- Cybersecurity testing
- Legal advice
- Regulatory certification
- Guaranteed productivity gains or ROI
Technical implementation can be separately scoped where appropriate.
Why Global AI Charter?
Business first
We start with the work — not the AI tool.
Vendor-neutral
Recommendations are based on organizational needs rather than a specific vendor.
Human-centered
Better human-AI collaboration, not indiscriminate automation.
Governance-aware
Risk, verification and accountability are considered alongside productivity.
Practical
Designed to be used by teams — not simply presented to executives.
Relationship with our other services
AI Readiness & Opportunity Assessment
Understand where the organization stands and where opportunities exist.
AI Strategy & Transformation Roadmap
Decide what should happen and in what order.
AI Productivity & Workflow Transformation
Turn priorities into redesigned ways of working. (You are here.)
AI Governance & Responsible Adoption
Build appropriate safeguards as AI adoption expands.
AI Workforce Enablement
Develop the skills required for sustainable adoption.
AI Advisory — All-in-One
For organizations requiring an integrated end-to-end engagement.
Frequently asked questions
What does AI workflow transformation actually involve?
It means examining how work currently happens, finding where AI can genuinely help, redesigning the workflow around effective human-AI collaboration, and defining how the change will be verified and measured — not simply handing teams a new tool.
How is this different from just giving employees ChatGPT or Copilot access?
Tool access alone doesn't change how work happens. Without workflow redesign, organizations typically see inconsistent usage, duplicated effort and unclear accountability. This service redesigns the underlying process, not just the toolset.
Will every task in our workflow be automated?
No. The objective is to determine what AI should do, what should remain human, and how the two should work together — using models ranging from human-led to controlled automation, depending on task, risk and consequence.
How much does an AI workflow transformation engagement cost?
Engagements start from ৳50,000 / $400 for a focused Workflow Discovery, up to ৳350,000 / $3,000 for Multi-Function Transformation. Enterprise engagements are custom-scoped based on the number of workflows, departments and technical requirements.
Do you guarantee productivity gains or ROI?
No. Productivity outcomes depend on organizational context, adoption and execution. We provide a measurement framework so effectiveness, quality, adoption and risk can be tracked honestly, rather than presenting hypothetical gains as guaranteed outcomes.
Is this service vendor-specific?
No. Recommendations are vendor-neutral and based on organizational needs rather than any specific AI platform.
What if our main concern is governance and risk, not productivity?
Start with AI Governance & Responsible Adoption instead. This workflow service assumes productivity and redesign are the primary goal, with governance considered alongside it.