Workbook: Building a sustainable data-driven organization, part 1

Unbundling AI: Building a sustainable data-driven organization | Introduction to the data transformation era | Workbook, part 1/5 | Week #2024-1

Hello,

This workbook is based on conversations with AI startup founders and engineers.
We present it as an evolving planner to help founders and leaders integrate the central notions of building a sustainable data-driven organization.

There are many ways to build business solutions and tools with AI, including open-source models, LLMs, training models, fine-tuning, or using hosted APIs, all from scratch. But we also see a surge of interest in data-driven business acquisitions among large companies. It entails buying an existing solution, not starting it from zero, with the potential for more autonomy and ownership.

Nevertheless, without adequately managing the integration processes, the venture can rapidly lead to slide into meltdown.

This workbook is a non-technical tool for structuring early conversations across the multiple roles needed to implement a Human-AI interactions when building a sustainability-focused system.

We are sharing the workbook on Substack as an inclusive tool for our premium members. It will be available for sale via our various platforms and websites.
If you haven’t already, you can subscribe now and enjoy being a Premium member of Wild Intelligence.

The following parts briefly explain the various perspectives we can obtain from the patterns expected by founders, entrepreneurs, and decision-makers in their data-related decision-making process.

The priority for organizations to build next-generation systems falls into three areas: 

• Improving data management; 

• Enhancing data analytics and machine learning;

• Expanding the use of all types of enterprise data, including streaming and unstructured data.

To help organizations become data-driven, the core business must be deployed on a wide adoption of data-driven systems, cloud-based technologies, including analytics tools with machine learning capabilities. 

All need to be supported by the ability to generate actionable insights.

Building a sustainable data-driven organization

1. Introduction to the data transformation era (what does it mean for the next generation business?) | This week’s post below

2. Perspectives for defensibility

3. Growth and resilience

4. Barriers to scale in a complex environment

5. AI technologies, democracy, and culture—conclusion: visions of the future.

Why a workbook?

We created the “Building a sustainable data-driven organization” workbook to empower teams to collaborate and plan across disciplines to implement Human-AI interactions best practices.

While engaging with startup founders and corporate teams, we observed that teams were most successful when they brought all disciplines to the table and planned for implementing guidelines for Human-AI interactions early in the development process.

An imbalance exists between “guidelines that are based upon the engineering more than the design,” and because implementing data-driven guidelines impacts the entire system, including the data and the models driving the organization, is imperative for any business.

What is needed to address the challenges of the new era is to explore all available resources to effectively define specificities and competitive advantages—which is too often forgotten by decision-makers.

We hope you have a good week; stay happy and healthy.

We appreciate your feedback. Please like this post, share it with your friends and colleagues.
Thanks again,

Yael, and al. 

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