It was over 5 years ago we started planning the Data Toboggan event. It has been great to see the event grow 3x and we have changed with the technology growth. We will be opening CfS shortly for the next event anticipated to be 31 January 2025.
The story of human progress is punctuated by revolutions, not just in technology, but in how we think, organize, and trust. From the steam engines of the 1840s to the generative models of the 2020s, each wave has promised liberation and delivered disruption. Today, as AI surges toward ubiquity, we must ask: what have we learned from past revolutions, and what must we safeguard before the bubble bursts.
There are four revolutions that resulted in significant change
where we can learn from the affects to help the AI revolution progress
unhindered.
|
Era |
Catalyst |
Impact |
Risk |
|
Industrial
Revolution (c. 1760 – 1840s) |
Steam power,
mechanization |
Mass
production, urbanization, labour displacement |
Exploitation,
unrest (e.g. Plug Plot Riots, 1842) |
|
Digital
Revolution (1950s – 1990s) |
Mainframes,
UK computing pioneers, PCs |
Automation,
global communication, software economies |
Surveillance,
fragmentation, digital exclusion |
|
Cloud
Revolution (2000s – 2020s) |
Virtualization,
SaaS, mobile-first |
Scalable
infrastructure, remote work, data centralization |
Vendor
lock-in, opaque governance, cyber risk |
|
AI Revolution
(2020s –) |
Foundation
models, generative AI |
Cognitive
automation, new interfaces, synthetic creativity |
Hallucinations,
bias, job loss, trust collapse |
The second revolution of computing was not just technical.
It redefined abstraction, logic, and control. From the UK’s early computing
pioneers to the rise of PCs, it laid the groundwork for cloud and AI. Yet it
also introduced new vulnerabilities: fragmented standards, digital inequality,
and the erosion of analogue memory.
Cloud as the Bridge: Infrastructure to Intelligence
Cloud computing connected digital and AI with its abstracted
hardware, centralized data, and the capabilities to scale with ease. But as
Satya Nadella emphasizes in his annual letter and Microsoft’s 2025 report,
innovation without strategic purpose is fragile. Microsoft’s Secure Future
Initiative and Quality Excellence Initiative reflect a shift: AI must be built
on trust, not just talent.
Brad Smith’s AI Diffusion Report warns that AI is spreading
faster than any prior technology but unevenly. The Global South, non-English
languages, and underrepresented communities’ risk being left behind.
Data: The Fuel, the Flaw, the Future
AI’s power is unprecedented and has the power to improve or
destroy depending on the algorithm development but also on the state of data.
Poor quality, biased, or ungoverned data leads to hallucinations,
misinformation, and systemic risk. As the BBC’s article on AI hallucinations
shows, even the most advanced models can confidently fabricate facts,
undermining journalism, science, and public trust. From the simplest things I
have seen AI fabricate data, which is written so well, to the untrained eye it
could be believed. Once the data is triangulated the output can be trusted. However,
the data sources quality, the prompts and data that is behind paywalls will
influence the outcome.
This is not a glitch it is a consequence of probabilistic
systems trained on imperfect inputs. Without rigorous data governance,
provenance tracking, and human oversight, AI becomes a mirror of our worst
assumptions.
When the Bubble Bursts: Coping with the AI Comedown
Every revolution has its reckoning. The Plug Plot Riots of
1842, the dot-com crash, and the decline of post-industrial towns all reveal
the cost of overhyped promises and underprepared systems. When the AI bubble
bursts whether through regulation, disillusionment, or economic correction, organizations
with strong data foundations, ethical frameworks, and human-centred design will
endure.
Those who chased novelty without governance will falter.
Satya Nadella’s mantra is “thinking in decades, executing in
quarters” is more than a business strategy. It’s a survival imperative. The AI
era demands long-term vision grounded in short-term accountability. That means:
- Investing in data quality and lineage as core
infrastructure
- Embedding responsible AI principles into every product and
process
- Preparing workers for augmentation, not just automation
- Designing for resilience, not just scale
Conclusion: From Revolution to Renaissance
The Industrial Revolution reshaped labour. The digital
revolution redefined logic. The cloud revolution scaled infrastructure. AI is
now rewriting cognition. but without trust, transparency, and governance, even
the most powerful tools will falter. As the socio-technical divide deepens and
ecological systems strain, the cost of inaction grows, and we risk accelerating
collapse socially and ecologically.
The disruption from AI is only just beginning. As Business
Insider quoted, “Elon Musk said AI will make desk jobs feel like when
workers used to make calculations by hand before the computer age.” This
echoes the upheaval of 1842, when industrialisation redefined labour.
If we want AI to be a renaissance, not a reckoning, we must
treat data as infrastructure, governance as strategy, and human ethics as
non-negotiable. The future isn’t just what we build; it’s what we’re willing to
steward.
We must draw a line: to protect data, embed meaningful
guardrails, and confront the human cost of displacement. That means planning
not only for the jobs we lose, but for the ones we must invent. It also means
addressing the widening continental divide in AI development and its cascading
impact on the environment and global economy.
'It's going to be really bad': Fears over AI bubble bursting grow in Silicon Valley
https://www.bbc.co.uk/news/articles/cz69qy760weo
Satya Nadella annual letter: Thinking in decades, executing in quarters
https://www.microsoft.com/investor/reports/ar25/index.htmlhttps://www.linkedin.com/pulse/my-annual-letter-thinking-decades-executing-quarters-satya-nadella-7orpc?utm_source=share&utm_medium=member_android&utm_campaign=share_via
Brad Smith https://aka.ms/AIDiffusionReport
Elon Musk says the AI 'supersonic tsunami' will eliminate desk jobs 'at a very rapid pace'
A new conference has arrived. The Microsoft SQL Community Conference, SQLCon 2026, is coming as part of the Microsoft Fabric Community Conference, 16-20 March 2026 in Atlanta.
It will be a premier level conference for data professionals, featuring 50 breakout sessions and 4 expert-led workshops covering SQL Server, Azure SQL, SQL in Fabric, SQL Tools, migration & modernization, optimization, database security, AI Apps with SQL and much more.
Register now https://sqlcon.us/
I wanted to take this opportunity to thank all those in the community who shared their condolence with us on the death of my mum and who celebrated the life of a remarkable person.
I particularly want to thank SQLBits for this year for making The SQLBits 2025 Charity, the main charity for the event with donations going to The National Museum of Computing
The National Museum of Computing is also a fantastic visitor attraction, recognised as one of England’s top 100 ‘irreplaceable places’, allowing visitors to follow the development of computing from the ultra-secret pioneering efforts of the 1940s, through the large systems and mainframes of the 1950s-70s, to the rise of personal computing in the 1980s and beyond. The museum hosts lots of events throughout the year and does not receive government or Heritage Lottery Funding. I feel it is important to preserve the past and help the museum with some ambitious projects in the future. If you missed the opportunity to donate there is a direct page where you can make donations.
I would also like to thank the #MVPCommunity and the team at #DataToboggan for there tremendous support during this time. #MVPBuzz
You can read more about my mum, Joan Frances Holt here
Thank you again my #sqlfamily #datafamily
The Cadence Alpine framework was created from rigorous academic research undertaken to understand best practices usage of data by Dr Victoria Holt FBCS. It was created before researchers had the option of using agentic AI. With the new Microsoft Researcher agent 'it helps you tackle complex, multi-step research at work, delivering insights with greater quality and accuracy than previously possible'. It was also created before 16 May 16, 2025 when 'OpenAI launched Codex, a new fully agentic AI coding assistant built into ChatGPT. Unlike traditional code autocomplete tools, Codex goes beyond being just a smart editor. Codex is OpenAI's series of AI coding tools that help developers move faster by delegating tasks to powerful cloud and local coding agents.'
The CODEX framework was named in 2017 based on transition and change into the digital age.
Cadence Alpine’s Strategic Compass for Data and AI Maturity
The CODEX is Cadence Alpine’s guiding framework. A strategic compass that helps organizations navigate the evolving terrain of data and AI. It is designed to assess maturity, uncover blind spots, and chart a path toward clarity, resilience, and innovation.
The CODEX Framework (2017)
CODEX in Practice
Together, these five Alpen Themes: Control, Control of Operations, Data, Expediently and X (Unpredictable Events) form a dynamic map, not a static checklist. They help Cadence Alpine, and its partners assess where they stand, where they’re vulnerable, and where they can lead.
• The CODEX framework isn’t a one-time climb. It is a cycle of elevation. Organizations revisit each layer as they grow, recalibrate, and lead. It is adaptive, shows emergent properties and can help with complex or chaotic business that are affected by environmental changes.
• It enables the mindset of controls for data governance
• It is in the right place for EIM and EDM to start management of data assets
• It helps to transform the Executive mindset
• To stop unknown destruction of data and AI decisions
• To identify the hidden cost of data with poor data quality, ineffective decision making, out of data and inconsistent and duplicate data. In addition these compliance failures can mount
• Increase ROI by reducing inefficiencies
• Enables a strong Data base for intelligent foundation of AI, analytics and governance
Each of its five Alpen Themes represents a vital elevation in the landscape of intelligent operations. Each Alpen Theme has many Subalpine Elements which enable the breadth of complexity to be examined. These are:
Control (Business)
Focus: Strategic alignment, governance, and stakeholder clarity
Purpose: Ensures that data and AI initiatives are rooted in business vision, ROI, and ethical control.
Key Themes: Stakeholder mapping, governance frameworks, cultural alignment, KPI integration
“This is the summit where business vision meets operational reality.”
Control of Operations
Focus: Technical execution, system resilience, and process integrity
Purpose: Maintains control over infrastructure, applications, and workflows to ensure reliable delivery.
Key Themes: Security, cloud architecture, orchestration, documentation, implementation
“The ridgeline where systems must hold firm under pressure.”
Data
Focus: Data quality, architecture, governance, and ethical stewardship
Purpose: Builds a foundation of trustworthy, accessible, and responsibly managed data.
Key Themes: Lineage, ownership, availability, responsible AI, metadata, cost control
“The bedrock beneath every intelligent decision.”
Expediently
Focus: Agility, learning, and adaptive intelligence
Purpose: Enables rapid response, shared understanding, and modular thinking across teams.
Key Themes: Microlearning, business glossaries, agile pods, architectural flexibility
“The switchbacks that allow us to move swiftly without losing balance.”
X (Unpredictable Events)
Focus: Resilience, foresight, and strategic adaptability
Purpose: Prepares the organization to absorb shocks, pivot under pressure, and lead through ambiguity.
Key Themes: Scenario planning, crisis communication, regulatory agility, thought leadership
“The weather system we must read, not resist.”
The strategic benchmark shows the business alignment index.
CODEX Business Alignment Index
The CODEX Ascent Is Iterative.
Philosophical View in Action
The CODEX enables the positioning across four forward-looking dimensions: Human in the Loop, Understanding Societal Impact, Economic Impact, and Learning Intelligence. This reflects how the company sees itself within each domain, based on its strategic framework and operational ethos.
SHEL Map
Each dimension is explained
Strategic Positioning Map Explained
A current positioning and aspirational direction are recorded each time the CODEX is run and mapped against other businesses in the same sector.
In Summary the CODEX is a strategic compass for navigating the evolving terrain of data and AI, guiding organizations through five Alpen Themes: Control, Control of Operations, Data, Expediently, and X (Unpredictable Events).
It enables businesses to assess maturity, uncover blind spots, and elevate their operational intelligence through iterative ascent and not a one-time climb.
Each theme contains Subalpine Elements that examine complexity across governance, agility, resilience, and ethical stewardship, forming a strong foundation for AI, analytics, and executive decision-making.
CODEX also positions organizations across four dimensions: Human in the Loop, Societal Impact, Economic Impact, and Learning Intelligence ensuring that intelligence grows responsibly and adaptively.
By identifying hidden costs, preventing destructive data practices, and aligning with EIM and EDM principles, the CODEX transforms executive mindset and increases ROI through strategic clarity and control.
