Dr Obay, Jalan Bangsar, Kuala Lumpur (2026)

30/10/2026

🚀 Microsoft 365 Copilot or Google Gemini: Which One Should Your Organisation Invest In?

As an AI trainer and consultant, I’m often asked by CEOs and business decision-makers for my advice on which Generative AI (GenAI) tools they should adopt in their organisations.

Interestingly, most of these conversations revolve around two popular platforms: Microsoft 365 Copilot and Google Gemini.

💡 My answer is always simple: It’s not about choosing the most powerful AI tool. It’s about choosing the right AI ecosystem that delivers measurable business value.

📊 The latest global research in 2026 tells an interesting story:

According to the 2026 Microsoft Work Trend Index and Boston Consulting Group (BCG):

🔹 58% of AI users say AI enables them to produce work they couldn't have created a year ago.

🔹 74% of surveyed frontline employees now use AI regularly, up 23 percentage points from 2025.

🔹 42% of regular AI users among frontline employees report saving at least 8 hours per week.

🔹 Yet, only 36% of surveyed employees feel they have received adequate AI upskilling.

These findings highlight an important reality: AI adoption is accelerating globally, but employee readiness and organisational transformation are still struggling to keep pace.

So, before investing in AI licenses for every employee, I usually encourage CEOs and decision-makers to consider five important factors:

✅ Existing ecosystem: Is the organisation primarily using Microsoft 365 or Google Workspace?

✅ Business needs: Which daily tasks and workflows can AI genuinely improve?

✅ Data security: How will sensitive organisational information be protected?

✅ Employee readiness: Do employees have the necessary skills to use AI effectively?

✅ Return on Investment (ROI): Can the organisation measure actual productivity improvements against the cost of AI adoption?

🎯 My recommendation?

Don't start by purchasing hundreds of AI licenses. Start with AI literacy, practical hands-on training, and a structured pilot programme. Then scale based on measurable business outcomes.

🎓 Speaking of practical AI adoption, I recently had the pleasure of conducting “Mastering Microsoft 365 Copilot Applications,” a hands-on training session focused on empowering participants to leverage Copilot across Microsoft 365 applications, enhance productivity, streamline daily workflows, and work smarter with AI.

🙏 A special thank you to Linia, MMT Universal Academy, and the entire team for the wonderful collaboration and support in making this training a success!

💡 Remember: AI transformation isn't measured by how many licenses an organisation purchases, but by how effectively its people turn AI capabilities into real business value.

24/10/2026

I was delighted to deliver “From Raw Data to Real-World AI: An End-to-End Machine Learning Workshop” at UCSI University, Malaysia.

During this four-hour, hands-on workshop, students explored the complete machine learning lifecycle:

• AI, machine learning and deep learning fundamentals
• Data collection, cleaning and exploratory data analysis
• Feature selection and data preparation
• Classification, regression and model evaluation
• Turning trained models into interactive applications for real-time predictions

Using Python and real-world-inspired e-commerce and electric vehicle datasets, participants transformed raw data into insights, compared machine learning models and experienced how an AI solution moves from experimentation towards deployment.

With lecturers, I also shared how Generative AI can support teaching, research and academic productivity—including effective prompting, literature exploration and the responsible use of AI with attention to accuracy, privacy, ethics, academic integrity and human oversight.

This experience reinforced how important it is to connect academia with industry. When classroom knowledge is combined with practical tools, realistic datasets and industry workflows, learners are better prepared to solve meaningful real-world problems.

My sincere thanks to Prof Dr. Chloe Thong for arranging and organising the event. Special thanks to Prof Shayla Islam and Asst. Prof. Ts. Dr. Ghassan ALDharhanin for having me.

I look forward to more meaningful collaboration with you all!

18/10/2026

🚀 From Raw Data to Real-World AI: An End-to-End Machine Learning Workshop!

Are you interested in Artificial Intelligence, Data Science, Machine Learning, and GenAI tools but unsure how to turn raw data into real-world AI solutions?

I'm excited to invite you to join me for a FREE, hands-on Machine Learning Workshop at UCSI University, Kuala Lumpur!

This workshop is designed to take you through the practical journey of building an AI solution, from understanding and preparing raw datasets to developing, evaluating, and deploying machine learning models.

💡 What will you learn?

✅ Understanding the end-to-end machine learning workflow
✅ Data preparation, cleaning, and preprocessing
✅ Exploratory Data Analysis (EDA) and data visualisation
✅ Building and evaluating machine learning models
✅ Understanding how AI models can be applied to real-world problems

✅ Buidling a fully atomated model using GenAI tools

📅 Date: Thursday, 22 October 2026
⏰ Time: 2:00 PM – 5:00 PM
📍 Venue: Breadboard Room, Block G, Level 11, UCSI University KL Campus
💰 Registration: FREE!

🎓 Who should attend?

Everyone is welcome! Whether you're an undergraduate or postgraduate student, academic, university staff member, working professional, or simply someone curious about AI and Machine Learning, this workshop is for you.

No advanced machine learning knowledge is required. Just bring your laptop, curiosity, and enthusiasm to learn!

📜 Certificates will be provided to participants.

I'm looking forward to sharing practical knowledge, real-world examples, and hands-on experiences with everyone.

🙏 Special thanks to UCSI, Assoc Prof Dr Chloe Thong, and the organising team for making this learning opportunity possible.

📌 Seats are limited! Register using the QR code on the poster.

Let's learn, explore, and transform raw data into real-world AI solutions together!

Feel free to share this opportunity with your friends, colleagues, and anyone interested in AI.

10/10/2026

🚀 Upskill Your Employees Before Hiring New Talent: Building an AI-Ready Workforce!

I recently had the pleasure of conducting Batch 2 of the two-day “General AI Tools for the Workplace” training programme, focusing on AI for Leadership and Workplace Productivity.

💡 One key message: Before hiring new talent to support AI transformation, organisations should invest in upskilling their existing employees.

Your current employees already understand your business, processes, and customers. Equipping them with practical AI skills can be more cost-effective and sustainable than continuously recruiting new talent.

Throughout the programme, participants explored five key areas:

✅ Understanding AI – Building essential AI knowledge and awareness.

✅ Generative AI for Productivity – Using AI to improve daily tasks, communication, and problem-solving.

✅ AI-Powered Research & Decision-Making – Accelerating research and making informed decisions.

✅ Workflow Automation – Automating repetitive tasks to improve efficiency.

✅ Building AI Applications – Creating simple web applications and practical automations.

Participants gained hands-on experience with Google AI Studio, Claude Artifacts, Manus, Kimi, ChatGPT Sites, Google Gemini, Gemini Notebook, and other AI tools.

It was rewarding to see participants progress from understanding AI concepts to actively building AI-powered solutions for workplace challenges.

🎯 My key takeaway:

AI transformation is not about replacing people. It is about empowering them to achieve more with the right tools and skills.

Organisations that invest in AI literacy and continuous upskilling can build more productive, innovative, and future-ready teams.

My sincere appreciation to GKK Consultants Philippines, Nor Syuhada Sahimi , and Alif Najman for their continued support in making Batch 2 a success.

Thank you to all participants for their enthusiasm and willingness to embrace AI!

27/09/2026

I recently had the pleasure of conducting the AI for Business Productivity with Generative AI course in Malaysia, designed to help professionals use Generative AI in practical, responsible, and business-focused ways.

The programme explored four key areas:

Module 1: Introduction to AI for Business Productivity
Participants developed a foundation in Artificial Intelligence and Generative AI, including their business applications and role in improving everyday productivity.

Module 2: AI for Communication and Business Documentation
We examined how AI can support clearer communication and accelerate the creation, refinement, and summarisation of professional documents.

Module 3: AI for Data Analysis, Business Applications and Productivity
Participants explored how AI can help analyse business data, identify useful insights, support decision-making, and improve day-to-day workflows.

Module 4: AI for Project Management and Business Automation
We discussed practical ways to use AI for project planning, task coordination, workflow improvement, and the automation of repetitive business processes.

A central message throughout the course was clear: effective AI adoption begins with identifying the right business problem, providing the right context, and applying human judgement to the output.

My sincere thanks to Trainocate Malaysia and Lee Kar Yee for the collaboration, coordination, and continued support in making this learning experience possible.

I look forward to supporting more organisations and professionals as they build practical Generative AI capabilities and prepare for the future of work.

26/09/2026

From ChatGPT prompts to AI-generated marketing campaigns — inside a day of hands-on Generative AI training.

I recently had the pleasure of delivering a full-day "Generative AI for Content" workshop for a corporate client in Kuala Lumpur, in partnership with MMT Universal Academy Sdn Bhd.
This wasn't a lecture — it was a hands-on sprint through the modern AI content stack:

✅ Module 1 — Introduction to Generative AI: demystifying AI vs. ML vs. DL vs. GenAI and where each fits into real content workflows
✅ Module 2 — AI Text Content with ChatGPT: structured prompting techniques for blogs, social posts, and marketing copy
✅ Module 3 — AI-Generated Images & Video: creative prompting and hands-on tools to produce captivating visuals and short-form video content
✅ Module 4 — The GREAT AI Challenge: teams built and pitched complete AI-powered content campaigns — landing pages, product concepts, and marketing collateral — in real time
✅ Module 5 — AI for Productivity: exploring Gemini Notebook, and Google AI Studio to streamline research, synthesis, and daily workflows

By the end of the day, participants didn't just learn about generative AI — they walked away with a repeatable prompting framework and a campaign they built themselves.

A huge thank-you to:
🙏 All the participants — your energy, curiosity, and willingness to experiment made this one of the most engaged sessions I've run this year
🙏 MMT Universal Academy Sdn Bhd for the trust and flawless organization
🙏 Ms. Shamini Chandran, whose behind-the-scenes coordination made the day run seamlessly.

I believe organizations should explore and master how tools like ChatGPT, Gemini Notebook, and Google AI Studio can speed up content production and boost team productivity, this is exactly the kind of corporate training I deliver — practical, hands-on, and customizable to your industry.

18/09/2026

What does it take to build a successful career in Data Science, Artificial Intelligence, or Computer Science today?

On 15 September 2026, I had the pleasure of delivering a session at Asia Pacific University of Technology & Innovation - APU titled “Hiring Trends in the Data Science and Computer Science Field.” The session connected technological developments with the realities of today’s job market.

We explored five key areas:
🔹 AI in modern workplaces
🔹 The resume-screening and recruitment funnel
🔹 Current hiring trends
🔹 Common mistakes made by applicants
🔹 Practical preparation for internships and graduate roles

I introduced the students to the relationship between Big Data, Data Science, Machine Learning, Deep Learning, Generative AI, large language models, automation, and emerging AI agents. We also discussed the current state of AI development, where the technology may be heading, and how these changes are reshaping careers—not only in technical roles, but across entire organisations.

One of my main messages was simple:
A degree can open the first door, but evidence of your abilities helps you move through it.
For students preparing to enter the job market, this means:
✅ Strengthening technical foundations in programming, statistics, databases, algorithms, and cloud technologies
✅ Building practical projects that solve real problems
✅ Maintaining a well-organised GitHub portfolio with clear documentation
✅ Developing a professional LinkedIn presence
✅ Tailoring each resume to the role instead of sending one generic version
✅ Understanding how recruiters and applicant-tracking systems screen applications
✅ Improving communication, teamwork, critical thinking, and data storytelling
✅ Using AI as a learning and productivity partner—without losing independent thinking

We also discussed an important shift in hiring: employers increasingly want candidates who can combine technical knowledge with business understanding, responsible AI awareness, adaptability, and the ability to explain complex ideas clearly.

My advice to every student is to start before feeling completely ready. Build a small project. Publish it. Explain your decisions. Ask for feedback. Improve it. Consistent, visible progress creates a much stronger professional story than a long list of tools without evidence of application.

Thank you to Asia Pacific University and the student organisers for the invitation, warm welcome, and engaging discussion. It was encouraging to see so much curiosity about Data Science, AI, Computer Science, and the future of work.
The future will reward those who keep learning, keep building, and know how to turn knowledge into meaningful impact.

13/09/2026

I recently had the pleasure of conducting a two-day General AI Tools for the Workplace course, focused AI for leaders and producivity, on helping professionals turn generative AI from an interesting concept into practical, everyday capability.

The programme combined AI fundamentals with hands-on practice across five key areas:

• Understanding Artificial Intelligence

• Using Generative AI for smarter task ex*****on

• AI for instant research and decision support

• AI workflow automation for productivity

• Building, deploying, and experimenting with first automations and web apps

Participants explored tools including Google AI Studio, Claude Artifacts, Manus, Kimi, ChatGPT Sites, and Google Gemini/NotebookLM, alongside other AI tools. The emphasis was on applying the right tool to real workplace needs: faster research, clearer communication, better decisions, streamlined workflows, and simple automation solutions.

The most valuable outcome was seeing participants move from learning about AI to actively building with it. AI productivity is not only about saving time—it is about enabling teams to focus more energy on meaningful, high-value work.

My sincere appreciation to GKK Consultants, Nor Syuhada Sahimi, Alif Najmannajman for their support and contribution in making this programme a success.

Thank you as well to all participants for the energy, curiosity, and willingness to experiment.

31/08/2026

Procurement is no longer only about negotiating prices—it is increasingly about using data intelligently, anticipating risk and making faster, better-governed decisions.

I recently had the pleasure of conducting an AI for Procurement course focused on turning artificial intelligence from an emerging concept into practical value for procurement professionals. 🤖

We began by building a clear understanding of AI in procurement and exploring the wider landscape of AI tools available to the profession.

The course then examined practical, industry-relevant applications, including:
📊 Spend analysis and cost optimisation
🤝 Supplier management and risk monitoring
📑 Contract management and negotiation support
⚙️ AI-enabled procurement workflow automation
🎯 Strategic decision-making for procurement leaders

Through practical discussions and activities, participants considered how AI can help identify spending patterns, uncover cost-saving opportunities, assess supplier risks, support contract-related decisions and reduce time spent on repetitive processes.

Importantly, adoption was not discussed in isolation. We also addressed responsible AI, ethics and compliance—including the need for data quality, appropriate governance, human oversight and accountable decision-making.
The objective was to equip participants with a clearer framework for identifying valuable AI use cases, evaluating tools responsibly and prioritising opportunities that align with genuine procurement challenges.

As a trainer, it was rewarding to see participants connect AI capabilities with their own procurement processes and consider where the technology could improve efficiency, productivity and decision quality.

I am grateful to Trainocate Malaysia for the opportunity to collaborate on delivering this timely and industry-relevant training.

AI will not replace sound procurement judgement. Used responsibly, however, it can strengthen that judgement by providing better insights, improving visibility and enabling professionals to focus more of their time on strategic value.

24/08/2026

Completing a course is always rewarding—but what stays with me most is not only what we teach, but the ideas, questions, and perspectives we exchange along the way. 🎓

I recently completed teaching Data Engineering at Taylor's University for the Master of Applied Computing programme, and it was another meaningful opportunity to connect academic foundations with the realities of today’s technology industry.

Throughout the course, we explored how modern Data Engineering has evolved from traditional Big Data architectures to increasingly flexible, scalable, and cloud-native ecosystems.

Students worked with concepts across the Hadoop ecosystem, including HDFS, MapReduce, Apache Hive, Apache Spark, and Apache Kafka, while also examining ETL/ELT pipelines, distributed processing, batch and streaming architectures, data lakes, and data warehouses.

At the same time, we discussed how organisations are implementing similar capabilities through modern Cloud Computing platforms, particularly AWS, Microsoft Azure, and Google Cloud Platform (GCP).

For me, the important question is never simply “How does this technology work?”

It is also:
When should we use it? Why would an organisation choose one architecture over another? How does it scale? And how can Data Engineering ultimately support Data Analytics, Artificial Intelligence, Machine Learning, and better business decisions?

This is where I believe the connection between academia and industry becomes increasingly important.

Technology is moving quickly. Cloud platforms, real-time analytics, automation, Generative AI, and modern data architectures are continuously reshaping how organisations build and manage their data ecosystems. Higher education therefore needs to evolve alongside these developments.

One of the things I value most about teaching is being with students—listening to their perspectives, challenging ideas, discussing real-world scenarios, sharing lessons from industry, and also learning from the questions they bring into the classroom.

Our goal should be bigger than preparing students for the next assignment or examination. It should be about preparing them to confidently address the real data challenges they will encounter in their careers.

Thank you to my students at Taylor's University for the discussions, curiosity, and energy throughout this journey.

Learning becomes more meaningful when academia, industry, and people come together to share knowledge and build the future.

Dr Obay

30/10/2026

24/10/2026

18/10/2026

10/10/2026

27/09/2026

26/09/2026

18/09/2026

13/09/2026

31/08/2026

24/08/2026

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