An end-to-end AI transformation for Hewar Group

Executive Summary

AI for CXOs and Board Members delivered to align leadership around AI strategy and opportunities.

Company-wide AI upskilling delivered across multiple employee cohorts.

Nine departments assessed through structured discovery sessions.

AI readiness and current-state reports produced department by department.

Business problems mapped to AI, technology, or process solutions.

Use cases prioritized through a cost-impact matrix and converted into a calendar roadmap.

KPIs and governance framework defined to support measurable and responsible execution.

Project Objectives

The program was designed around three core objectives

Build AI understanding and alignment at leadership level. Hewar’s leadership team needed to understand the strategic implications of AI, the latest tools, the risks and opportunities, and the role AI could play in transforming the business.

Upskill the full organization. Employees across departments needed practical AI skills, especially prompt engineering and AI-assisted productivity, to help them use AI in their daily work.

Create a practical AI transformation roadmap. The company needed a clear, prioritized, and measurable roadmap showing which business problems should be solved, which use cases should be implemented first, what tools or approaches should be used, and how success should be measured.

Phase 1: Executive AI Training

The engagement began with a dedicated AI for CXOs and Board Members training session for Hewar’s leadership team. This session created a shared executive language around AI and ensured that the leadership team could sponsor the transformation from an informed and strategic position.

• The current state of artificial intelligence
• The strategic implications of generative AI
• How AI is transforming marketing, PR, communications, and professional services
• The latest state-of-the-art AI tools
• AI opportunities for productivity, creativity, automation, and decision support
• The risks, limitations, and governance requirements of AI adoption
• How leaders should think about AI strategy and organizational transformation

Phase 2: Company-Wide AI Upskilling

Following the leadership session, Cognit DX delivered wider AI training for Hewar’s employees across multiple cohorts. The purpose of this phase was to equip the entire staff with practical AI skills that could immediately improve their day-to-day work.

The training focused on prompt engineering, AI-assisted productivity, and practical applications of AI across knowledge work, communications, marketing, client servicing, creative production, operations, and internal support functions.

• Drafting and improving written content
• Generating campaign ideas
• Summarizing and structuring information
• Building proposals and presentations
• Accelerating research
• Improving client servicing workflows
• Supporting creative ideation
• Analyzing information and extracting insights
• Improving speed, quality, and consistency of daily deliverables

Phase 3: Departmental Discovery and Current-State Assessment

The training phase was followed by a structured discovery and assessment phase. Cognit DX conducted a dedicated two-hour discovery session with each department. In total, the assessment covered nine departments, including editorial, social media, client servicing, legal, HR, finance, and other core business and support functions.

During these sessions, Cognit DX worked with each department to understand

• Day-to-day activities and workflows
• Operational processes and business pain points
• Repetitive tasks, manual processes, and bottlenecks
• Current usage of AI tools
• Current level of digital and AI readiness
• Opportunities for AI, automation, integration, or process improvement
• At the end of the discovery stage, Cognit DX produced two important outputs

AI Readiness Assessment: a department-by-department view of Hewar’s current AI maturity, capability, usage patterns, and readiness for transformation.

Current-State Report: an “as-is” view of the organization, documenting how departments currently operate, where friction exists, and which business problems should be addressed.

Phase 4: AI Strategy Development

After the discovery stage, Cognit DX developed an AI strategy for Hewar by defining a future end state in which the organization could operate as a more AI-powered, efficient, creative, and scalable business.

Importantly, the strategy did not start with technology. It started with the business. Cognit DX worked backwards from department-level problems and executive priorities to identify the right solutions. Some solutions involved AI. Others involved technology without AI, such as system integration, digitization, or workflow automation. Some were non-technical solutions, such as process reengineering, bureaucracy reduction, or operational streamlining.

For each department, Cognit DX identified

• The most important business problems
• The root causes behind those problems
• The recommended solution for each problem
• Whether the solution required AI, non-AI technology, or process improvement
• The expected business value
• The relative cost and complexity of implementation

In parallel, Cognit DX also reviewed a list of priority business problems provided by Hewar’s executive leadership and applied the same solution-mapping methodology.

Phase 5: Use Case Identification and Solution Mapping

The discovery and strategy phases produced a longlist of business problems and corresponding solutions. Each solution was categorized based on its primary nature:

AI solution: where artificial intelligence could directly solve or improve the problem.

Technology solution: where digitization, integration, or workflow automation was more suitable than AI.

Process solution: where the best answer involved redesigning processes, reducing friction, removing bureaucracy, or changing ways of working.

This categorization helped Hewar avoid the common trap of treating AI as the answer to every problem. Instead, the company received a balanced transformation roadmap that used AI where AI made sense, and used other forms of improvement where they were more appropriate.

Phase 6: Cost-Impact Matrix and Prioritization

To prioritize the use cases, Cognit DX developed a structured cost-impact matrix. Each proposed solution was scored across two dimensions: cost score and impact score.

• Cost Score
• The cost score was calculated as a weighted average of three factors
• Human cost
• Time cost
• Financial cost
• Impact Score
• The impact score was calculated as a weighted average of five factors
• Impact on revenue growth
• Impact on cost reduction
• Impact on customer satisfaction
• Impact on employee satisfaction
• Impact on compliance with government regulations and internal policies

Each solution was then plotted on a matrix using cost and impact as its two coordinates. The matrix was divided into four quadrants:

• Quadrant
• Meaning
• Recommended Action
• High Impact / Low Cost

Quick wins with strong value and manageable effort.

Implement first; typically Q1 priorities.

High Impact / High Cost

Strategic initiatives requiring more investment, planning, and resources.

Spread across Q2, Q3, Q4, and beyond.

Low Impact / High Cost

Initiatives requiring significant effort without enough business value.

Deprioritize or avoid.

Low Impact / Low Cost

Low-risk opportunistic improvements.

Handle when capacity allows or assign to junior teams/interns.

Phase 7: AI Transformation Roadmap

Once all use cases were scored and prioritized, Cognit DX converted the cost-impact matrix into a practical execution roadmap. The roadmap translated the prioritization logic into a calendar-based implementation plan, showing when each solution should be executed and how initiatives should be sequenced.

• Which use cases should be implemented in Q1
• Which strategic projects should be spread across Q2, Q3, Q4, and beyond
• Which initiatives could be handled opportunistically
• Which initiatives should not be pursued
• How to balance quick wins with longer-term transformation projects
• How to pace implementation based on internal capacity and business impact

Phase 8: Tools, Approaches, KPIs, and Governance

For each prioritized solution, Cognit DX provided a short description of the recommended approach, including the tools, platforms, or implementation methods that could be used.

Cognit DX also defined KPIs and success metrics for the use cases, ensuring that implementation could be measured against clear baselines.

• Reducing proposal turnaround time
• Reducing the number of revision cycles for key deliverables
• Reducing the number of people required to complete a specific task
• Increasing the number of deliverables produced per creative per week
• Improving speed of content production
• Improving quality and consistency of client-facing outputs
• Reducing operational bottlenecks
• Improving compliance and internal governance
• Increasing employee productivity

Examples of measurable targets included increasing proposal production speed by 25%, reducing revision cycles from five to two, reducing required contributors from three people to one, and increasing creative output per employee by 50%.

Finally, Cognit DX provided a governance framework to support responsible and sustainable AI adoption. This helped Hewar define how AI should be used, monitored, managed, and scaled across the company.

• Final Deliverables
• Leadership AI training
• Company-wide AI upskilling
• Departmental discovery sessions
• AI readiness assessment
• Current-state assessment report
• Department-by-department business problem mapping
• Executive priority mapping
• AI, technology, and process solution recommendations
• Cost-impact scoring methodology
• Cost-impact matrix
• Prioritized use case portfolio
• Calendar-based AI transformation roadmap
• Recommended tools and implementation approaches
• KPIs and measurement framework
• AI governance framework
• End-to-end AI strategy document

Key Impact

The project helped Hewar Group move from AI interest to AI execution readiness. Through this engagement, Hewar gained:

• A leadership team aligned around AI strategy
• A workforce equipped with practical AI productivity skills
• A clear understanding of departmental AI readiness
• A documented current-state view of business operations and pain points
• A prioritized portfolio of transformation initiatives
• A roadmap showing what to implement, when, and why
• Clear KPIs to measure success
• A governance framework for responsible AI adoption

The project demonstrated Cognit DX’s ability to go beyond training and deliver a full AI transformation advisory engagement, connecting people, process, technology, strategy, and governance into one practical roadmap.

Strategic Value

The Hewar Group AI Transformation Program is a strong example of how Cognit DX helps organizations move from AI awareness to structured AI transformation.

The engagement did not begin with tools or technology. It began with the business: the problems departments face, the priorities leadership cares about, and the operational outcomes the company wants to improve.

By combining executive education, workforce upskilling, AI readiness assessment, use case identification, cost-impact prioritization, KPIs, and governance, Cognit DX helped Hewar Group build a practical and measurable path toward becoming an AI-powered organization.

This case study shows Cognit DX’s ability to deliver not only AI training, but also AI strategy, transformation planning, and execution readiness for ambitious organizations in fast-moving sectors such as marketing, PR, communications, and professional services.