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Shelly Palmer - Building Your First Synthetic Employee

Shelly Palmer has been named LinkedIn’s “Top Voice in Technology,” and writes a popular daily business blog.
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Illustration created by DALL-E with the prompt “Create a 16×9 image for this blog post.”

What would it take to build your company’s first synthetic employee? What AI models could you use? How much data will it require? What about compute power? Electricity? Technical resources? Security? Legal? Risk? Ethics? Is the idea simply too crazy to think about now? Should you just wait until someone invents artificial general intelligence (AGI)?

Over the past year, I’ve had the pleasure of leading several workshops on this very subject for some of our global clients. Some key takeaways:

  1. You don’t need AGI to do this.
  2. Getting everyone aligned on what it will take to turn AI into a competitive advantage is invaluable.
  3. The exercise will help you organize all the disparate AI projects that are already in progress across your organization.

Hallway Handle

If you work in a large organization, “our first synthetic employee” will become the “hallway handle.” (That’s the way people passing in the hallway will refer to your project.) Imagine two colleagues passing each other in the hallway. Without stopping to chat, they begin a very short dialog: “Hey Joe!” “Yo! John.” “What are you working on?” “The synthetic employee project.” “Yeah, I heard about that. That’s awesome!” This kind of alignment and cross-company label can serve as an excellent north star for the project.

Synthia (Synthetic + Intelligence Advanced)

Back to the job at hand. Let’s outline some of the things that must come together to create “Synthia,” your company’s first synthetic employee.

Core Functions and Capabilities

    • Advanced Decision Making: Uses deep learning models to make strategic business decisions based on real-time global economic data, market trends, and internal business analytics.
    • Autonomous Problem Solving: Equipped with reinforcement learning algorithms that adapt over time, enabling the AI to solve complex business challenges independently.
    • Natural Language Processing (NLP): State-of-the-art NLP capabilities allow Synthia to understand, respond, and generate human-like text for communications, reports, and presentations. This includes multilingual support to communicate and operate globally.
    • Multimodal LLM: (Which would probably handle all of the required NLP.) Integrates and interprets various data types — including text, images, and audio — to understand and process complex information from diverse inputs, enhancing decision-making and interaction capabilities across different mediums.
    • Predictive Analytics: Utilizes machine learning models to predict market changes, customer behavior, and supply chain disruptions.
    • Personalization Engines: Tailors marketing strategies and customer interactions based on individual consumer data analysis.
    • Robotic Process Automation (RPA): Automates routine and complex tasks across all departments (such as finance, HR, and operations) to improve efficiency and accuracy.
    • Computer Vision: Processes and analyzes visual data from the environment to aid in tasks such as quality control, surveillance, and customer interaction in retail settings.
    • Emotional Intelligence: Uses affective computing to understand and react to human emotions, enhancing customer service and employee interactions.
    • Ethical AI Governance: Monitors and ensures that all AI operations adhere to ethical AI standards and compliance with global regulations.

Data Requirements

  • 0th Party Data (Directly from the source)

      • Internal Business Operations Data: Real-time access to company databases and sensors for operations, finance, HR, production, etc.
      • Employee Input: Direct feedback and inputs from employees via custom apps or internal systems.

Integration and Security

Ethics and Compliance

Should You Wait For AGI?

Synthia represents a first pass at an additive theory of AI integration. The strategy is to start with tested individual tools and build your synthetic employee as if you were building with Lego bricks. Though primitive by comparison to what’s coming, a system like this has the potential to dramatically enhance operational efficiency, decision-making speed (and accuracy), and customer satisfaction. Are you ready to start the process? We’re here to help.

Author’s note: This is not a sponsored post. I am the author of this article and it expresses my own opinions. I am not, nor is my company, receiving compensation for it. This work was created with the assistance of various generative AI models.

  • 1st Party Data (Directly collected from users)

    2nd Party Data (Partner data)

    3rd Party Data (Externally acquired)

      • Customer Interaction Data: Data collected from websites, apps, and physical locations (e.g., stores, kiosks) about customer preferences, behaviors, and feedback.
      • User-Generated Content: Insights from customer reviews, social media interactions, and other forms of user-generated content.
      • Strategic Partner Data: Shared data from partnerships (like supply chain information, co-developed technology insights, and market analysis).
      • Industry Benchmarking: Data shared through alliances or consortiums for benchmarking and best practices.
      • Market Data: Data purchased from market research firms, financial data services, and economic analysts.
      • Competitive Intelligence: Data about competitors’ activities, sourced from legal and ethical intelligence services.
      • Global and Regional Regulations: Updates on regulations that impact various aspects of business, sourced from regulatory bodies and legal services.
    • Hybrid Cloud Infrastructure: To ensure scalability and security, leveraging both private and public cloud services.
    • Advanced Cybersecurity Measures: Use of encryption, anomaly detection, and AI-driven threat intelligence systems to protect sensitive data and operations.
    • AI Ethics Board: Establishment of a board to oversee ethical AI use, ensuring that Synthia operates under strict ethical guidelines to avoid biases and respect privacy.
    • Regulatory Compliance Monitoring: Automated systems to keep up with global regulations and ensure compliance.

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ABOUT SHELLY PALMER

Shelly Palmer is the Professor of Advanced Media in Residence at Syracuse University’s S.I. Newhouse School of Public Communications and CEO of The Palmer Group, a consulting practice that helps Fortune 500 companies with technology, media and marketing. Named  he covers tech and business for , is a regular commentator on CNN and writes a popular . He's a , and the creator of the popular, free online course, . Follow  or visit .