Summary - AdviceTech Podcast 105 – Scrybd

In the fast-evolving landscape of financial services, professionals seek new tools to enhance client experiences, reduce administrative burdens, and uphold rigorous compliance standards. One increasingly powerful set of technologies—automation and artificial intelligence (AI)—promises exactly these benefits. Yet as exciting as these developments can be, the ethical and professional dimensions must remain central. This article explores how AI-driven meeting note automation, workflow integration, and advanced data processes can transform financial advisory practices, all while maintaining the highest levels of integrity, professionalism, and client protection.

Drawing insights from a recent conversation between Host Patrick Gardner—Head of Technology at Collins SBA—and Guest Speaker Kohl Gianoli—Director of InSource Automation and Founder of Scribed—this piece will illuminate practical use cases, highlight key considerations around ethics and compliance, and offer a roadmap for how advisors can responsibly integrate AI in their businesses. Although AI offers immense promise, it is equally vital that practitioners handle it prudently to protect client information, maintain trust, and satisfy legal and regulatory requirements.

1. The Modern AI Landscape in Financial Services

1.1. From Manual File Notes to AI-Powered Transcripts

For decades, financial advisors and other professionals have dedicated countless hours to creating meeting notes, transcripts, and follow-up documents. Historically, these tasks were tedious and prone to human error—especially under pressing deadlines. Even automated transcription tools, once considered revolutionary, often lacked the ability to interpret context or generate meaningful summaries.

Now, however, advanced language models such as OpenAI’s GPT series, including ChatGPT, have elevated routine documentation into a realm of richer context, actionable insights, and ready-to-use outputs. Gianoli’s own product, Scribed, reflects this evolution. Scribed is a Software as a Service (SaaS) platform that can ingest audio files or transcripts, then produce templated summaries, letters, or meeting notes tailored to specific industries, including financial planning.

1.2. Why Advisors Are Embracing AI Meeting Notes

The financial sector, particularly financial planning, stands at the intersection of high-value client relationships and complex compliance obligations. Documenting the rationale behind advice and ensuring accurate records of discussions can be pivotal to meeting Australian Securities and Investments Commission (ASIC) requirements or other regulatory mandates worldwide.

AI-driven solutions address these needs by automating the creation of consistent, compliant notes. Instead of devoting 30-45 minutes after every meeting to recall details and manually craft file notes, advisors can use a recorded audio session that automatically generates a professional summary. The process typically takes just a few minutes to review before storage or further distribution. By minimizing administrative overhead, professionals regain time for critical, human-centered work such as client relationship-building and strategic planning.

1.3. A Snapshot of Ethical and Professional Imperatives

With these benefits come significant responsibilities:

1. Data Privacy and Security: Ensuring clients’ sensitive financial and personal information remains safe is non-negotiable. Any platform used must employ robust encryption, secure hosting, and compliant data governance practices.
2. Accuracy and Reliability: AI might occasionally “hallucinate” or generate inaccurate information when the prompts are unclear or the data is inadequate. Advisors must diligently review all AI-produced material.
3. Regulatory Alignment: File notes, summary emails, and compliance documentation must align with the legal framework within which the advisor operates. AI can streamline compliance, but only if the underlying models and input-output structures follow relevant guidelines.
4. Client Trust: A misstep with AI—whether through a data breach or inaccurate records—can undermine years of painstakingly built client confidence. Engaging transparently about the use of AI is essential for sustaining trust.

2. Meeting Kohl Gianoli: A Passion for Automation

2.1. Professional Journey and Motivation

Originally beginning his career in a different industry (electrical wholesaling) and later earning a Master of Banking and Finance, Gianoli discovered a passion for process optimization while working at a financial planning and accounting group. As Operations Manager, he recognized that unnecessary manual tasks were robbing professionals of time and mental bandwidth.

Gianoli saw these repetitive processes as not merely inconveniences, but opportunities to leverage technology. He founded InSource Automation to help small businesses harness Microsoft’s Power Platform—particularly Power Automate (for connecting different applications without writing code) and Power Apps (for building custom applications)—to streamline workflows. From there, he began building specialized note-taking and templating solutions for each new client.

2.2. The Birth of Scribed

After devising custom meeting-note solutions for multiple clients, Gianoli noticed a recurring theme: the outputs—template-based summaries and consistent file notes—were nearly identical from project to project. While advanced customizations were occasionally required, the core logic remained the same. This realization inspired him to develop Scribed as an all-purpose, industry-agnostic SaaS product.

In its current form, Scribed is a lightweight tool offering three core categories of templates:

1. Universal Templates: Generic structures such as summary emails, basic CRM notes, or internal team meeting recaps.
2. Industry-Specific Templates: For instance, financial advisors can draw on specialized compliance-based frameworks (e.g., annual review file notes, risk profile discussions).
3. Organizational Templates: For those requiring unique or branded reports, Scribed can incorporate a specific house style or content sequence that seamlessly fits into existing workflows.

By emphasizing simplicity and affordability, Gianoli aims to make AI-driven note-taking accessible to smaller firms and solo operators who might otherwise be deterred by the high monthly fees of competing platforms.

3. Building a Culture of Ethical Automation

3.1. Defining Professionalism and Ethics in an AI-Powered World

Professionalism and ethics in financial services go hand in hand with competence, transparency, and accountability. Integrating AI requires close attention to these core principles, recognizing that automation tools:

• Extend Human Judgment: AI should never override the professional’s expertise. Instead, it augments it.
• Operate Under Rigorous Compliance Requirements: The creation of file notes, for example, must ensure that every relevant point in a client conversation is accurately captured.
• Preserve Client-Centered Service: Technology should free advisors from menial tasks, thereby allowing them to spend more time listening to clients and solving more complex challenges.

3.2. Common Ethical Pitfalls and How to Avoid Them

1. Data Usage Without Explicit Consent
   • Pitfall: Recording a meeting or storing transcripts in the cloud without notifying the client or obtaining formal permission.
   • Solution: Always explain how meeting data will be used and stored, and secure explicit consent in writing if local regulations require it.
2. Incomplete or Inaccurate File Notes
   • Pitfall: Relying entirely on AI transcripts without cross-checking for factual errors or missing context.
   • Solution: Maintain final accountability by reviewing each AI-generated note, ensuring critical details—like fees, disclaimers, or client objectives—are correctly documented.
3. Overstepping Confidentiality Boundaries
   • Pitfall: Sharing confidential data for training AI models or storing sensitive information on non-compliant third-party servers.
   • Solution: Rely on providers with proven security measures, and if self-hosting or using a private model, ensure encryption, restricted user access, and frequent security audits.
4. Biased or Unfair Outputs
   • Pitfall: Relying on large language models that might harbor subtle biases, leading to suggestions or summaries that disadvantage certain client segments.
   • Solution: Where possible, utilize custom AI models trained on balanced data sets; verify that the resulting file notes or summaries do not reflect unintended biases.

4. Harnessing Microsoft’s Power Platform for Efficiency

4.1. Power Automate: Connecting Data with Integrity

A critical aspect of automation is consolidating or moving information between different systems in a seamless, verifiable way. Power Automate—part of Microsoft’s Power Platform—is a low-code/no-code solution that can connect a firm’s email system, CRM, calendaring tool, cloud storage, and more. For example:

• New Client Intake: When a prospective client submits an inquiry via Microsoft Forms, Power Automate instantly creates a record in the CRM and triggers a welcome email—complete with scheduling links.
• Fact-Finding: Advisors can replace email-based questionnaires with dynamic Microsoft Forms. The data is then routed to the CRM, generating a fresh client record without the need for re-keying data.
• Internal Document Approvals: Power Automate can handle multi-step approvals to ensure that compliance or managerial reviews happen in the right sequence, with each step logged automatically.

From an ethical standpoint, these automations reduce manual errors and ensure consistent adherence to processes—important components of compliance. Still, it remains essential that advisors implement the correct checks and balances, verifying that each automated workflow is functioning as intended.

4.2. Power Apps: Tailor-Made Solutions for Specialized Needs

For practices needing highly customized workflows or interfaces, Power Apps allows non-developers to build simple mobile or web applications. Imagine a compliance app that:

• Pulls Current Client Data from the CRM.
• Shows a Decision Tree for annual review (e.g., “Has the client’s risk appetite changed?”).
• Prompts for Next Actions such as scheduling a review meeting or requesting updated financial statements.

These applications can augment existing CRMs or software solutions. They do not replace them, but fill gaps in specialized processes or handle corner cases that might be difficult to manage within a more rigid system.

4.3. Ethical Safeguards: Testing, Training, and Governance

While Power Automate and Power Apps offer immense flexibility, they also place considerable power in the hands of end-users. Before launching any automation, it is crucial to:

1. Thoroughly Test Scenarios: Simulate real client data, ensuring accuracy, completeness, and privacy.
2. Train Staff Properly: Even no-code/low-code tools have learning curves. Inadequate training can lead to misdirected automation or unintentional data exposures.
3. Implement Governance: Document each automation, specify who can access or modify it, and maintain a log of changes. This governance protects both the firm and its clients.

5. The Future of AI: Structured Outputs and Custom GPTs

5.1. Moving Beyond “Hallucination”: Guaranteed Formats

Early AI systems sometimes returned unpredictable outputs, known as “hallucinations,” where the system created fictional names, emails, or tasks. However, new iterations of GPT-like models are significantly improving the consistency of responses—particularly through “structured output” methods. These methods ensure that the AI adheres to rigid schemas or formats.

Why does this matter for financial services? Structured output allows for more trustworthy automations:

• Consistent Data Mapping: If the tool expects a client name, date of birth, and risk profile, the AI consistently provides them in the correct format.
• Reduced Manual Verification: Advisors spend less time combing through AI summaries for possible mistakes.
• Enhanced Reliability: Combining AI’s generative abilities with a structured framework ensures that compliance-driven processes—like record-keeping—are both fast and accurate.

5.2. The Rise of Custom GPTs: Tailoring Models to Firm Data

Beyond improved reliability, the next frontier lies in custom GPTs, where an AI model is specifically trained or “fine-tuned” on a firm’s proprietary data or on a curated knowledge base. For example, a wealth management firm could train a custom GPT on:

• Historic Client Interactions: Summaries and key interactions that highlight best practices and standard procedures.
• Product Disclosure Statements (PDS): So that answers about particular products are instantly verifiable and up to date.
• Regulatory Guidelines: The system can reference exact compliance text to ensure annual review notes or advice summary letters meet local rules.

With a custom GPT, an advisor can pose specific queries—like “What does our guidance say on early access to superannuation for hardship cases?”—and receive direct, accurate answers citing the internal compliance manuals. The potential savings in time are huge, but only if the data is well-structured, current, and ethically managed.

5.3. Ethical Implications of Advanced AI

As AI models become increasingly embedded in daily workflows, the ethical stakes rise:

1. Fair Use of Proprietary Data: Firms must clarify ownership and usage rights of the data used to train models, particularly if the data contains client information.
2. Transparency with Stakeholders: Clients should be informed that certain processes—like file note generation—are automated. This fosters trust rather than suspicion.
3. Bias Scrutiny: If a model is trained primarily on certain types of clients or limited product sets, it could unintentionally produce advice that disadvantages minority or niche groups.
4. Accountability Frameworks: Firms must remain vigilant in how they monitor, audit, and correct AI outputs.

6. Practical Use Cases and Cautions

6.1. File Notes and Compliance Documents

AI-driven file note tools like Scribed effectively streamline meeting documentation. When an advisor concludes a meeting, they can upload a voice memo, the tool transcribes and summarizes the discussion, and the advisor spends a few minutes validating or amending any details. With custom templates, the final note can automatically include disclaimers about general advice, references to relevant product documents, or signature lines.

From an ethical lens, it is crucial to ensure:

• Storage Security: The final notes are stored in a way that meets data protection regulations (e.g., encrypted SharePoint, or a secure CRM).
• Full Disclosure: Clients, particularly in jurisdictions requiring recorded consent, know that their conversation is captured and how it is retained.
• Regular Quality Checks: Firms might designate a compliance officer to spot-check AI-generated notes to ensure they remain accurate.

6.2. Internal Team Meetings and SOP Generation

In addition to client-focused notes, automation tools prove beneficial for internal operations. Teams can record a weekly meeting and produce a standardized set of action items, departmental priorities, or updates for later reference. Tools like Scribed even transform these summaries into Standard Operating Procedures (SOPs), saving valuable administrative time.

On the ethics side, leaders should still be mindful of:

• Data Minimization: Only record what is necessary. Team members should also be aware that their comments may be transcribed and shared.
• Inclusivity: Ensure that using AI does not replace genuine communication or lead to scenarios where in-person collaboration is deprioritized.
• Accuracy and Follow-through: Summaries are only as good as the final actions. If an AI summary calls for cross-department coordination, there must be a human in charge of verifying that tasks get done.

6.3. Marketing and Thought Leadership

Another example Gianoli mentioned is generating LinkedIn posts or marketing content based on quick voice memos captured on the go. Advisors who build a personal brand by sharing market insights or financial tips may find this particularly useful.

However, marketing content carries its own ethical considerations:

• Compliance with Advertising Regulations: Public communications must avoid misleading or unsubstantiated claims about investment performance or product suitability.
• Relevance and Value: AI can help produce a draft, but the final content must genuinely serve and inform the audience, rather than serve as clickbait.
• Protecting Client Confidentiality: Do not inadvertently disclose any personalized client scenarios, even if anonymized, unless proper permissions are obtained.

7. Navigating Compliance and Professional Standards

7.1. Data Protection and Regulatory Constraints

The conversation between Patrick Gardner and Kohl Gianoli repeatedly underscores the importance of robust data protection. Whether leveraging Microsoft’s Power Platform or third-party AI tools, professionals must comply with:

• Australian Privacy Principles (APPs) and ASIC Requirements: For Australian financial advisors.
• General Data Protection Regulation (GDPR): For those handling data pertaining to EU residents.
• Other Regional Regulations: Such as FINRA in the United States or the FCA’s guidelines in the United Kingdom.

To ethically harness AI, a thorough due diligence process is essential. Firms should check:

1. Encryption Standards
2. Server Locations (Data sovereignty laws)
3. Incident Response Plans in case of data breaches
4. Third-Party Data-Sharing Agreements ensuring that vendors cannot misuse client data

7.2. Transparency and Informed Consent

Professionalism also requires transparency. Before using AI transcription or summarization tools in client meetings, advisors should discuss:

• What is Being Recorded: Whether the entire audio or just key points are captured.
• How it is Stored and Used: Who has access, retention periods, and the potential for future data queries.
• Potential Risks: Outline the remote possibility of data leaks or AI errors, while assuring clients that rigorous protections and human reviews are in place.

Obtaining explicit, written consent will solidify trust. Although disclaimers in engagement letters can suffice, best practice involves reinforcing these points verbally so clients can ask questions or opt out if they feel uncomfortable.

7.3. Continual Professional Development (CPD)

As technology evolves, so must the skill set of the modern financial advisor. Regulatory bodies increasingly require advisors to stay updated on emerging technologies and data protection standards. Incorporating AI and automation into a firm’s culture demands ongoing CPD that addresses:

• Tools Training: Learning advanced features of platforms like Power Automate or custom GPTs.
• Ethics Updates: Understanding case studies of AI misuse in finance, exploring how to avoid them, and staying ahead of new ethical frameworks.
• Client Communication Best Practices: Scripted ways to explain AI usage in initial client meetings, ensuring clarity.

8. The Road Ahead: Balancing Innovation with Integrity

8.1. AI as a Catalyst for Better Advice

The true promise of AI in financial planning is not to replace human expertise but to liberate professionals from low-value, repetitive tasks. As Gianoli points out, tools like Scribed allow an advisor to finish a meeting, record a quick voice memo, and receive a full, structured file note—complete with disclaimers—in just a few minutes. This efficiency translates into more time spent analyzing portfolio strategies, understanding client aspirations, or engaging in proactive client outreach.

8.2. Overcoming Implementation Challenges

Common obstacles include:

• Cost and Complexity: Some AI platforms charge high monthly fees, or require specialized IT knowledge. Tools designed for smaller firms, such as Scribed, aim to remove cost barriers with simplified, transparent pricing.
• Staff Reluctance or Inexperience: In many organizations, employees fear AI may be too complex or reduce human roles. Managers can mitigate these fears by investing in skill-building, clarifying that AI is a supplement, not a replacement.
• Ethical Considerations: In some cases, advisors may lack familiarity with best practices in data governance. Ongoing training, robust compliance checks, and a culture of open dialogue address this gap.

8.3. Staying Client-Centric

Whether generating a brief email, an extensive file note, or a compliance document, a professional’s primary aim remains serving the client. Every technological upgrade should be measured against its contribution to that purpose. If an AI-driven workflow shortens response times or improves the thoroughness of advice documents, it aligns with client interests. Conversely, if a new tool creates confusion, fosters doubt, or jeopardizes client privacy, it fails to meet acceptable standards of ethics and professionalism.

9. Conclusion: Charting a Responsible Path Forward

As AI technologies mature, financial advisors have a remarkable opportunity to improve service quality, ease operational burdens, and maintain rigorous regulatory compliance. Meeting note automation stands out as a “quick win,” epitomizing how a once time-consuming process can become a near-instant solution. Yet harnessing AI responsibly goes far beyond installing a new app or uploading audio recordings. It demands a nuanced understanding of data security, client consent, and the complexities of integrated workflows.

Professionalism in the AI Era
The conversation between Patrick Gardner and Kohl Gianoli highlights a simple yet profound truth: AI is not inherently a substitute for professional judgment, but an enhancement that can empower experts to do their jobs more effectively. At the same time, ignoring vital considerations around data protection, informed consent, and regulatory compliance can negate these benefits. True professionalism in today’s market means seamlessly blending technology with a dedication to ethical standards.

Ethics as the North Star
While advanced AI offers an exciting glimpse into the future—where structured outputs, custom GPTs, and frictionless integrations become standard—the road to that future is paved with ethical choice points. Only by taking a client-centric, transparent, and security-conscious approach can advisors fully realize the potential of these tools. Every step—from adopting new platforms to training staff—should be guided by the question: “Does this serve the best interests of our clients and uphold our professional obligations?”

Invitation to the Profession
By embracing automation responsibly, financial advisors can redirect more energy into nuanced problem-solving, relationship-building, and strategic guidance—ultimately enhancing client outcomes. Whether you are a firm with one advisor or a multi-office operation, the key is to start small, remain vigilant, and aim for continuous improvement. As more solutions like Scribed, Power Automate, and Power Apps evolve, the financial services sector will be better equipped to deliver timely, compliant, and genuinely impactful advice.

In summation, the union of AI-driven automation and financial services holds extraordinary promise. By weaving in ethical frameworks and a commitment to client well-being at every juncture, firms of all sizes can revolutionize their practices—prompting a new era where efficiency and integrity are not just compatible, but mutually reinforcing. It is up to today’s professionals to seize the moment, champion transparency, and ensure that each innovation stands on the bedrock of trust and accountability.

Disclosure and Disclaimer
This article is based on a podcast discussion intended for professional financial advisors. The content is for general informational purposes, not formal advice. Before acting on any AI-related or automation advice, evaluate its relevance and suitability for your circumstances, and consult qualified professionals. In addition, always review any platform’s Product Disclosure Statement (PDS) or equivalent documentation to ensure compliance and alignment with your firm’s risk management protocols. AI tools must be used responsibly, with particular care taken to protect sensitive client data and maintain adherence to the highest standards of professionalism and ethics.

Accreditation Points Allocation:

0.10 Technical Competence

0.10 Client Care and Practice

0.10 Regulatory Compliance and Consumer Protection

0.10 Professionalism and Ethics

0.40 Total CPD Points