Last week, we hosted three webinars for audiences in EMEA, the Americas and Asia Pacific, exploring the practical applications of AI in business decision-making. Across these sessions, we covered AI fundamentals, its impact on organisations, real-world case studies, and essential skills for leveraging AI effectively. We also fielded numerous questions—both live and pre-submitted—that highlighted the most pressing concerns and opportunities AI presents today. Here's a summary for those who missed it (more to come!)...
We began with an overview of AI’s evolution, distinguishing between traditional AI and generative AI. Traditional AI follows rules and recognises patterns, while generative AI can create new content, from text to images and even music. We demonstrated how models like ChatGPT, Gemini, and Claude work, emphasising that selecting the right AI depends on business needs rather than just technical superiority.
We explored multiple studies indicating that AI adoption can increase productivity by 14–59%, improve quality control by over 30%, and boost employee engagement significantly. These insights reinforce that AI isn’t just a trend—it’s a fundamental shift in how businesses operate.
While AI offers significant benefits, it also comes with risks. We discussed the dangers of hallucination (AI generating false information), data privacy concerns (such as Samsung’s infamous data leakage incident), and how to mitigate these risks through clear governance, policy frameworks, and responsible AI usage.
A live demonstration showcased how AI can assist in:
Content generation: Creating reports, policies, marketing plans, and sales strategies.
Data analysis: Extracting insights from complex financial documents.
Process automation: Streamlining administrative and customer service tasks.
Strategic decision-making: Enhancing leadership effectiveness through AI-powered insights.
We received numerous questions from participants, covering a wide range of topics. Below are the key questions and our responses:
Q: How can AI assist in financial document analysis and decision-making?
A: AI can automate financial data extraction, identify trends, and support forecasting by analysing patterns. It reduces manual effort in audits, compliance checks, and risk assessments.
Q: Can AI replace support functions like HR and procurement?
A: AI enhances these functions rather than replacing them. HR teams use AI for recruitment screening, while procurement benefits from AI-driven contract analysis and supplier risk assessment.
Q: How can expert freelance content writers leverage AI to get more business?
A: Freelancers can use AI for research, content structuring, and drafting, allowing them to take on more projects efficiently. AI can also provide insights on SEO trends and content personalisation to extend their online reach.
Q: My company has banned AI due to security concerns. How can I convince leadership to adopt it securely?
A: Companies can implement secure AI policies by using private, enterprise-level AI models that do not share data externally. AI literacy training for leadership also helps bridge the gap between risk and opportunity.
Q: How do we dispel the notion that using AI is ‘cheating’ and get older staff to embrace productivity gains?
A: Position AI as a tool that augments expertise rather than replaces it. Providing use-case examples and hands-on training helps employees understand its value.
Q: What’s the difference between new Chinese AI models and existing Western models? Is it cheaper?
A: Chinese AI models are cost-effective but currently less advanced than ChatGPT or Gemini. However, they provide strong competition, pushing overall AI innovation forward. Understand where your data is going before using them - for example, DeepSeek, like OpenAI free versions, uses your prompt data for training their model.
Q: How can companies secure their investment in AI infrastructure for both quick ROI and long-term gains?
A: Organisations should start with pilot projects to demonstrate ROI before scaling AI adoption. Ensuring AI models align with business strategy is crucial for long-term success.
Q: How do investment management firms explore AI opportunities across departments?
A: Start with AI-powered analytics for risk assessment and automation for client interactions. Training employees to use AI in investment research enhances firm-wide adoption.
Organisations that experiment with AI in targeted use cases and who train their users see the fastest returns. AI literacy, governance, and structured implementation plans are essential for sustainable success.
We appreciate everyone who attended and contributed their insights. If you're interested in learning more about AI adoption, governance, and training, reach out to us for tailored AI strategy workshops. Stay tuned for our next AI series!
Would you like a personalised AI adoption plan or to be notified of upcoming webinars? Contact us today.