Like the Greek god Zeus, many enterprises today are rooted in order-driven, rule-based systems, with task and workflow-defined processes, and a focus on ‘people-centric sense and respond know-how.’
An ‘Intelligent Enterprise’ in the Age of AI mirrors the Greek god Prometheus—a symbol of adaptability, learning, and evolution, where data-driven, AI-enabled decision-making thrives.
The journey from Zeusian order to a Promethean enterprise is a journey that promotes agency for action while placing safeguards to ensure no harm is done, both in lockstep.
Here are five aids for this walk to an “intelligent” enterprise for tomorrow:
1. Supporting Culture
A supportive environment is essential for sustainable change. AI is a transformational technology and employees must buy in for the enterprise to benefit. While corporate leadership, consultants, and technology firms extol AI’s benefits and invest heavily in infrastructure, muted production successes and employee concerns about technology, job security, and workload stress hinder adoption.
To foster an employee-supportive culture if not already done:
2. Employee First Use Case Approach for Gen AI Implementation and Customer First for More Established Machine Learning, Data Sciences
Generative AI (Gen AI) is a new technology with unique abilities—integrating all types of data (internal, external, structured, unstructured) and proactively generating insights. However, it also comes with challenges related to bias, reliability, explainability, and data security.
Prioritize employee-focused Gen AI use cases to:
Mature technologies like machine learning and data science can directly support customers or operational teams with a customer-facing use case.
3. Bi-Modal Exploration (AI Enhanced and AI Driven)
The agency and engine for change could be seen as bi-modal in nature with short, medium, and long term goals.
AI Enhanced: Permeate and enhance key existing processes with AI with a diffusion by infusion model to eventually cover all key processes.
AI Driven: Start now for long-term fence and form model to create new AI-driven experiences.
4. Save IT Opex, Invest First, Build evidence-driven ROI retroactively for Future
There are few precedents and even fewer validated models (everyone has a theory of course!) for making a ROI business case for AI-enhanced or driven processes. At the same time, enterprises have financial constraints and requirements in this uncertain time.
Instead of overthinking or over-engineering the ROI, a possibly quicker way to progress would be to:
5. Do No Harm
Just as the pharmaceutical industry operates under a “do no harm” principle, AI-enhanced or AI-driven processes must follow the same rule.
“Do no harm” means:
To ensure these standards are met, there should be centralized governance overseeing AI-enhanced or AI-driven initiatives, with mandatory approvals and veto rights.
Enterprises, despite their complexities and size, have done very well to embrace technology disruptions in the last several decades. There was no Internet thirty years ago, and today there is very little that is not Internet-facing. The Internet changed the enterprise unimaginably.
There is no reason that AI will not do the same to today’s Internet enterprise — to be fully Intelligent, made by the people and for the people.
I hope these insights help.
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Best wishes
II. Questioning / Asking
Good conversations flow from well‑sequenced questions—topical, simple, coherent, cohesive.
LLM Conversation Example 1
Q: What are empirical judgments?
A: Empirical judgments are based on observation, experience, or experimentation.
Q: What are moral judgments?
A: Moral judgments are based on ethical principles and values.
