ARTIFICIAL INTELLIGENCE
An AI-native strategy firmGlobal Advisors: a consulting leader in defining quantified strategy, decreasing uncertainty, improving decisions, achieving measureable results.
A Different Kind of Partner in an AI World
AI-native strategy
consulting
Experienced hires
We are hiring experienced top-tier strategy consultants
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
PODCAST: Effective Transfer Pricing
Our Spotify podcast discusses how to get transfer pricing right.
We discuss effective transfer pricing within organizations, highlighting the prevalent challenges and proposing solutions. The core issue is that poorly implemented internal pricing leads to suboptimal economic decisions, resource allocation problems, and interdepartmental conflict. The hosts advocate for market-based pricing over cost recovery, emphasizing the importance of clear price signals for efficient resource allocation and accurate decision-making. They stress the need for service level agreements, fair cost allocation, and a comprehensive process to manage the political and emotional aspects of internal pricing, ultimately aiming for improved organizational performance and profitability. The podcast includes case studies illustrating successful implementations and the authors’ expertise in this field.
Read more from the original article.
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: Nate B Jones
“The pleasant surprise is how much you can accomplish when you properly harness your agents, and how big companies are leaning in and able to actually get volume done on that basis.” – Nate B Jones – AI News & Strategy Daily
Context of the Quote
This quote from Nate B Jones captures a pivotal moment in the evolution of AI agents within enterprise settings. Delivered in his AI News & Strategy Daily series, it highlights the unexpected productivity gains when organisations implement AI agents correctly. Jones emphasises that major firms like JP Morgan and Walmart are already deploying these systems at scale, achieving high-volume outputs that traditional software cycles could not match1,2. The core insight is that proper orchestration-combining AI with human oversight-unlocks disproportionate value, countering the hype-driven delays many companies face.
Backstory on Nate B Jones
Nate B Jones is a leading voice in enterprise AI strategy, known for his pragmatic frameworks that guide businesses from AI hype to production deployment. Through his platform natebjones.com and Substack newsletter Nate’s Newsletter, he distils complex AI developments into actionable insights for executives1,2,7. Jones produces daily video briefings like AI News & Strategy Daily, where he analyses real-world use cases, warns against common pitfalls such as over-reliance on unproven models, and provides custom prompts for rapid agent prototyping2,4.
His work focuses on bridging the gap between AI potential and enterprise reality. For instance, he critiques the ‘human throttle’-where hesitation and risk aversion limit agent autonomy-and advocates for decision infrastructure like audit logs and reversible processes to build trust3. Jones has documented production AI agents at scale, urging leaders to act swiftly as competitors gain ‘durable advantage’ through accumulated institutional intelligence2. His library of use cases spans finance (e.g., JP Morgan’s choreographed workflows) to operations, emphasising that agents excel in ‘level four’ tasks: AI drafts, humans review, then AI proceeds1. By October 2025, his briefings were already forecasting 2026 as a year of job-by-job AI transformation5.
Leading Theorists and the Subject of AI Agents
AI agents-autonomous systems that perceive, reason, act, and learn to achieve goals-represent a shift from passive tools to proactive workflows. Nate B Jones builds on foundational work by key theorists:
- Stuart Russell and Peter Norvig: Pioneers of modern AI, their textbook Artificial Intelligence: A Modern Approach defines rational agents as entities maximising expected utility in dynamic environments. This underpins Jones’s emphasis on structured autonomy over raw intelligence1,3.
- Andrew Ng: Dubbed the ‘Godfather of AI,’ Ng popularised agentic workflows at Stanford and through Landing AI. He advocates ‘agentic reasoning,’ where AI chains tools and decisions, aligning with Jones’s production playbooks for enterprises like Walmart2.
- Yohei Nakajima: Creator of BabyAGI (2023), an early open-source agent framework that demonstrated recursive task decomposition. This inspired Jones’s warnings against hype, stressing expert-designed workflows for complex problems1,4.
- Anthropic Researchers: Their work on Constitutional AI and agent patterns (e.g., long-running memory) informs Jones’s analyses of scalable agents, as seen in his breakdowns of reliable architectures6.
Jones synthesises these ideas into enterprise strategy, arguing that agents are not future tech but ‘production infrastructure now.’ He counters delays by outlining six principles for quick builds (days or weeks), including context-aware prompts and risk-mitigated deployment2. This positions him as a practitioner-theorist, translating academic foundations into C-suite playbooks amid the 2025-2026 agent revolution.
Broader Implications for Workflows
Jones’s quote underscores a paradigm shift: AI agents amplify top human talent, making them ‘more fingertippy’ rather than replacing them1. Big companies succeed by ‘leaning in’-auditing processes, building observability, and iterating fast-yielding volume at scale. For leaders, the message is clear: harness agents properly, or risk irreversible competitive lag2,3.
References
1. https://www.youtube.com/watch?v=obqjIoKaqdM
2. https://natesnewsletter.substack.com/p/executive-briefing-your-2025-ai-agent
3. https://www.youtube.com/watch?v=7NjtPH8VMAU
4. https://www.youtube.com/watch?v=1FKxyPAJ2Ok
5. https://natesnewsletter.substack.com/p/2026-sneak-peek-the-first-job-by-9ac
6. https://www.youtube.com/watch?v=xNcEgqzlPqs
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