Should you let Gen AI decide?
𝐒𝐡𝐨𝐮𝐥𝐝 𝐲𝐨𝐮 𝐥𝐞𝐭 𝐆𝐞𝐧 𝐀𝐈 𝐝𝐞𝐜𝐢𝐝𝐞?
"Building Agentic Organizations" Part 1: Why Bespoke Decision Science is Key to Responsible Agentic AI.
In our last post, we highlighted how agentic ecosystems revolutionize organizations by automating workflows and augmenting human roles.
Today, let's explore a key consideration: how templated agents powered by LLMs can overlook the unique nuances of an organization's culture and processes, and why integrating custom decision science can elevate their impact.
Templated workflows from generic platforms sound convenient, but they often lack the nuance of your company's unique culture, processes, and the critical decision making that differentiates your company and drives client value. This can lead to irresponsible implementations (think risks like hallucinations, mis-prioritized actions, or recommendations that don't actually align with your business realities.)
For Instance:
𝐖𝐡𝐞𝐧 𝐬𝐡𝐨𝐮𝐥𝐝 𝐚𝐧 𝐚𝐠𝐞𝐧𝐭 𝐞𝐱𝐞𝐜𝐮𝐭𝐞 𝐚 𝐬𝐩𝐞𝐜𝐢𝐟𝐢𝐜 𝐭𝐚𝐬𝐤?
𝐖𝐡𝐲 𝐬𝐡𝐨𝐮𝐥𝐝 𝐢𝐭 𝐩𝐫𝐢𝐨𝐫𝐢𝐭𝐢𝐳𝐞 𝐨𝐧𝐞 𝐨𝐮𝐭𝐜𝐨𝐦𝐞 𝐨𝐯𝐞𝐫 𝐚𝐧𝐨𝐭𝐡𝐞𝐫?
𝐇𝐨𝐰 𝐜𝐚𝐧 𝐢𝐭 𝐜𝐨𝐧𝐟𝐢𝐝𝐞𝐧𝐭𝐥𝐲 𝐫𝐞𝐜𝐨𝐦𝐦𝐞𝐧𝐝 𝐭𝐡𝐞 𝐧𝐞𝐱𝐭 𝐛𝐞𝐬𝐭 𝐚𝐜𝐭𝐢𝐨𝐧?
At MUDRICK & ASSOCIATES, we address this by building bespoke AI agents infused with tailored machine learning models, coupled with robust checks and balances. This "decision-science" layer ensures agents not only automate trivial tasks but also make informed, value-driving decisions that represent the value that your organization brings to your clients.
Our high-level process empowers this transformation:
1.) 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 𝐚𝐧𝐝 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐌𝐚𝐩𝐩𝐢𝐧𝐠: Uncover opportunities in your data ecosystem.
2.) 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐦𝐞𝐧𝐭 𝐨𝐟 𝐭𝐡𝐞 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐋𝐚𝐲𝐞𝐫: Create custom agents (stateless, memory-enabled, multi-agent, etc.) that integrate seamlessly.
3.) 𝐂𝐮𝐬𝐭𝐨𝐦 𝐌𝐋 𝐌𝐨𝐝𝐞𝐥𝐬: Embed bespoke algorithms to mitigate risks and enhance accuracy.
4.) 𝐓𝐚𝐬𝐤 𝐀𝐮𝐠𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧: Handle everything from file organization to proactive and predictive analytics.
5.) 𝐆𝐚𝐦𝐢𝐟𝐲 𝐇𝐮𝐦𝐚𝐧 𝐅𝐞𝐞𝐝𝐛𝐚𝐜𝐤 𝐋𝐨𝐨𝐩 𝐚𝐧𝐝 𝐐𝐀: Keep humans in the loop for oversight, ensuring ethical and effective outcomes.
The impact? Across industries these agents can optimize forecasting, personalize recommendations, identify next-best customers, and drive efficiency in departments from operations to sales, creating measurable value and augmenting human roles to make us all more effective.
As AI fiduciaries, we're paid based on the results we deliver, aligning our success with yours.
Stay tuned for Part 2, where we'll explore high-level examples of agentic AI in action across key business functions.
What are your biggest concerns with implementing agentic AI in your organization?
