ARTIFICIAL INTELLIGENCE
An AI-native strategy firmGlobal Advisors: a consulting leader in defining quantified strategy, decreasing uncertainty, improving decisions, achieving measureable results.
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Quantified Strategy
Decreased uncertainty, improved decisions
Global Advisors is a leader in defining quantified strategies, decreasing uncertainty, improving decisions and achieving measureable results.
We specialise in providing highly-analytical data-driven recommendations in the face of significant uncertainty.
We utilise advanced predictive analytics to build robust strategies and enable our clients to make calculated decisions.
We support implementation of adaptive capability and capacity.
Our latest
Thoughts
Podcast – The Real AI Signal from Davos 2026
While the headlines from Davos were dominated by geopolitical conflict and debates on AGI timelines and asset bubbles, a different signal emerged from the noise. It wasn’t about if AI works, but how it is being ruthlessly integrated into the real economy.
In our latest podcast, we break down the “Diffusion Strategy” defining 2026.
3 Key Takeaways:
- China and the “Global South” are trying to leapfrog: While the West debates regulation, emerging economies are treating AI as essential infrastructure.
- China has set a goal for 70% AI diffusion by 2027.
- The UAE has mandated AI literacy in public schools from K-12.
- Rwanda is using AI to quadruple its healthcare workforce.
- The Rise of the “Agentic Self”: We aren’t just using chatbots anymore; we are employing agents. Entrepreneur Steven Bartlett revealed he has established a “Head of Experimentation and Failure” to use AI to disrupt his own business before competitors do. Musician will.i.am argued that in an age of predictive machines, humans must cultivate their “agentic self” to handle the predictable, while remaining unpredictable themselves.
- Rewiring the Core: Uber’s CEO Dara Khosrowshahi noted the difference between an “AI veneer” and a fundamental rewire. It’s no longer about summarising meetings; it’s about autonomous agents resolving customer issues without scripts.
The Global Advisors Perspective: Don’t wait for AGI. The current generation of models is sufficient to drive massive value today. The winners will be those who control their “sovereign capabilities” – embedding their tacit knowledge into models they own.
Read our original perspective here – https://with.ga/w1bd5
Listen to the full breakdown here – https://with.ga/2vg0z
Strategy Tools
Strategy Tools: The 7S Framework – A Comprehensive Guide
By John Khova Global Advisors digital consultant Introduction The McKinsey 7S Framework is one of the most enduring and widely recognised management models in strategic consulting and organisational design. It posits that organisational effectiveness depends not on...
Fast Facts
Fast Fact: Great returns aren’t enough
Key insights
It’s not enough to just have great returns – top-line growth is just as critical.
In fact, S&P 500 investors rewarded high-growth companies more than high-ROIC companies over the past decade.
While the distinction was less clear on the JSE, what is clear is that getting a balance of growth and returns is critical.
Strong and consistent ROIC or RONA performers provide investors with a steady flow of discounted cash flows – without growth effectively a fixed-income instrument.
Improvements in ROIC through margin improvements, efficiencies and working-capital optimisation provide point-in-time uplifts to share price.
Top-line growth presents a compounding mechanism – ROIC (and improvements) are compounded each year leading to on-going increases in share price.
However, without acceptable levels of ROIC, the benefits of compounding will be subdued and share price appreciation will be depressed – and when ROIC is below WACC value will be destroyed.
Maintaining high levels of growth is not as sustainable as maintaining high levels of ROIC – while both typically decline as industries mature, growth is usually more affected.
Getting the right balance between ROIC and growth is critical to optimising shareholder value.
Selected News
Quote: Alap Shah – Lotus CIO, Citrini report co-author
“Sectors that we think have real risk [from AI] are generally intermediation sectors.” – Alap Shah – Lotus CIO, Citrini report co-author
Alap Shah, Chief Investment Officer at Lotus Technology Management and co-author of the influential Citrini Research report The 2028 Global Intelligence Crisis, issued this stark warning amid growing market unease over artificial intelligence’s transformative power. In a Bloomberg Podcast interview on 24 February 2026, Shah highlighted how AI agents could dismantle business models reliant on intermediation – sectors that profit from facilitating transactions between parties.1,2,4
Alap Shah’s Background and Expertise
Alap Shah serves as CIO at Lotus Technology Management, a firm focused on navigating technological disruptions in global markets. His insights stem from deep experience in investment strategy and emerging technologies. Shah co-authored the Citrini report, a hypothetical scenario that vividly depicts AI’s potential to trigger economic upheaval by 2028. The report, which spread rapidly online, sparked what Shah termed the ‘AI scare trade selloff’, contributing to global share declines and sharp drops in sectors like Indian IT services.1,3,5
Shah’s analysis emphasises AI’s capacity to erode ‘friction-based’ moats. He points to companies like DoorDash (food delivery), American Express (payment processing), Uber Eats, and real estate agencies, where customer loyalty hinges on switching costs and habitual use. AI agents, running on devices with near-zero marginal costs, can instantly compare options, verify reliability, and execute transactions, bypassing intermediaries.1,2,4
The Citrini Report: A Hypothetical Crisis Scenario
Published by Citrini Research, The 2028 Global Intelligence Crisis outlines a timeline beginning in mid-2027 with AI-driven defaults in private equity-backed software firms, escalating to widespread intermediation collapse. Key triggers include agentic AI for coding (a ‘SaaSpocalypse’ shifting value from SaaS providers to in-house tools) and shopping agents like Qwen’s open-source model, which pit providers against each other and eliminate fees such as 2-3% card interchange rates.2,4
The report predicts a ‘ghost GDP’ from mass white-collar layoffs – potentially 5% within 18 months in the US – creating a negative feedback loop: job cuts reduce spending, pressuring firms to invest more in AI, accelerating disruption. Sectors at risk include finance, insurance, software-as-a-service (SaaS), consumer platforms, and India’s $200 billion IT exports, where AI coding agents undercut low-cost labour.1,4,5,6
India faces particular vulnerability, with the report forecasting an 18% rupee depreciation and IMF discussions by Q1 2028 as services surplus evaporates.5 Real estate commissions compressed dramatically, dubbed ‘agent on agent violence’, as AI replicates agent knowledge.4
Shah’s Policy Prescriptions
To avert downturn, Shah urges taxing AI ‘windfall gains’ or inference compute, funding transfers for displaced workers via proposals like the ‘Transition Economy Act’ or ‘Shared AI Prosperity Act’. Beneficiaries include chipmakers, data centres, and AI labs like OpenAI, though Shah and critics debate surplus capture.1,3,4,6
Leading Theorists on AI Disruption and Intermediation
Shah’s views build on economists and thinkers analysing platform economics and automation:
- Erik Brynjolfsson and Andrew McAfee (MIT): In The Second Machine Age (2014), they argue digital technologies disproportionately boost skilled workers while automating routine tasks, widening inequality – a precursor to Citrini’s white-collar focus.[No specific search result; general knowledge]
- Vitalik Buterin: Ethereum co-founder, referenced in critiques for decentralised trust solutions (e.g., crypto verification) to replace marketplaces, aligning with AI agents breaking oligopolies.2
- Zvi Mowshowitz: In his Substack analysis of Citrini, he critiques surplus distribution, arguing ubiquitous agents commoditise intermediation without labs like OpenAI retaining cuts long-term.2
- David Autor (MIT economist): His research on automation’s polarisation effect (hollowing middle-skill jobs) informs fears of white-collar daisy chains in correlated productivity bets.[No specific search result; general knowledge]
These theorists underscore AI’s dual nature: efficiency gains versus systemic risks, echoing Shah’s call for intervention.2
Market Reaction and Ongoing Debate
The report’s release fuelled unease, with Nifty IT dropping 3.6% and broader selloffs. Shah expressed surprise at the scale but views white-collar US jobs as the litmus test over five years, given their 75% share of discretionary spending.3,5,6
References
1. https://www.startuphub.ai/ai-news/technology/2026/ai-s-scare-trade-fuels-market-unease
2. https://thezvi.substack.com/p/citrinis-scenario-is-a-great-but
4. https://www.citriniresearch.com/p/2028gic
!["Sectors that we think have real risk [from AI] are generally intermediation sectors." - Quote: Alap Shah - Lotus CIO, Citrini report co-author](https://i0.wp.com/globaladvisors.biz/wp-content/uploads/2026/02/20260224_20h00_GlobalAdvisors_Marketing_Quote_AlapShah_GAQ.png?w=1080&ssl=1)
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