The smart edge with Mehdi Faraji ACCA

Building Income Security in Uncertain Economies

In uncertain economies, income becomes fragile. Inflation rises. Markets fluctuate. Policies shift. But one thing remains constant: Your earning power depends less on the economy and more on how you position yourself within it. In this episode, we’ll talk about how professionals can build income security through diversified skills, global earning strategies, smart positioning, and certifications that still hold value.

Why Accountants Who Ignore AI Will Struggle in 3 Years

Automation and AI are just buzzwords They are transforming the finance world

How Professionals Stay Productive During National Instability

In this episode: 1 – Controlling Inputs 2 – Protecting Cognitive Energy 3 – Skill-Building During Uncertainty 4 – Long-Term Positioning vs Short-Term Panic   Periods of national instability test more than economies: They test focus. They test emotional control. They test long-term thinking. Therefore, you must :           Regain the momentum           Allocate some time for pressure and anxiety relief           Revise the strategic plans and address any likely drift Segment 1 – Controlling Inputs In times of instability, information becomes overwhelming.  News cycles accelerate. Rumors spread faster than facts.Emotional reactions multiply.  But high-level professionals understand one rule:  You cannot control national events. You can control your inputs.   Segment 2 – Protecting Cognitive Energy    Cognitive energy is your most valuable currency during instability.  Segment 3 – Skill-Building During Uncertainty   History shows something interesting. Those who invest in skills during unstable periods emerge stronger when stability returns.   While others react, you build.  Segment 4 – Long-Term Positioning vs Short-Term Panic Instability triggers survival thinking. But professionals must also think strategically.

One Finance Workflow and How AI Changes It

One Finance Workflow and How AI Changes It Workflow focus: Month-End Close Seven minutes to close the month, or seven hours of paperwork… which would you choose? It seems a silly question, but it requires setting up AI engines to automate long hours of repetitive tasks. In this episode, we will find an appropriate approach to answer the following question correctly: Would you rather achieve a highly accurate month-end close in just seven minutes or spend hours buried in reconciliation paperwork? To give an overall understanding of what is being clarified, we move in the following route: 1. Classic approaches to month-end procedures 2. AI-assisted procedures 3. Required controls 4. Final takeaway Month-end close is where finance teams lose sleep. Long hours, repetitive checks, pressure from management—and now AI is entering the picture. Since it has already been proven how practical AI is, the question isn’t whether AI can help, but how to use it without losing control. 1. The Traditional Month-End Close • Data extraction from ERP • Excel reconciliations • Manual variance analysis • Email back-and-forth • Drafting management explanations at 11 pm Key pain points: • Time pressure • Human error • Inconsistent explanations • Over-reliance on Excel “This is where finance teams burn energy—not insight.” 1. The AI-Assisted Month-End Close Where AI fits safely: • Data summarisation • AI reviews exports and highlights unusual movements • Variance explanations (first draft) • AI proposes explanations based on historical patterns • Checklist validation • AI compares close steps vs prior months • Management report drafting • AI creates a structured narrative, not a final judgment AI does the first pass. Humans keep the pen. 1. Controls You Must Keep (Very Important) • Human review layer is non-negotiable • No blind acceptance of AI outputs • Clear documentation: what AI touched and what humans approved • Sensitive data rules (what can and cannot go into AI tools) If AI makes your close faster but weaker, you’ve failed. 1. Final Takeaway • AI compresses time, not responsibility • Finance professionals who master AI + controls will lead • The future isn’t AI vs finance—it’s AI-augmented finance

How PTE Can Teach SMEs the Application of AI

How SMEs Can Apply the AI Engine Used by PTEWhen we talk about artificial intelligence, most people imagine big tech companies, massive budgets, and complex systems far beyond the reach of small businesses. But one of the most practical and successful AI engines in the world is already operating quietly in education — the AI behind the PTE exam.Today, I want to explore how the logic of that system can be applied not just to language testing, but to small and medium-sized businesses that want to worksmarter, faster, and more consistently. Common Mistakes SMEs Should Avoid Blind automation, unclear data structures, and unrealistic expectations often lead to AI failure. PTE succeeded because it prioritized consistency over perfection. Step-by-Step AI Adoption Roadmap for SMEs Step 1: Identify repetitive decisions Step 2: Define evaluation criteria Step 3: Standardize data inputs Step 4: Deploy AI as an assistant Step 5: Continuously review and improve Conclusion The success of PTE’s AI engine shows that AI is not exclusive to large corporations. SMEs can apply the same principles to scale expertise, reduce costs, and gain competitive advantage.