Two global reports reveal how nations and organisations are progressing with AI and what leaders can do to move from awareness to action.
Recently I have reviewed global AI benchmarks to better understand this complex landscape.
For leaders, benchmarks matter. They provide transparency, create shared understanding of where progress is being made, and help identify gaps.
Increasingly, technologists are being encouraged to develop more AI benchmarks, while executive leaders are urged to adopt them as tools to improve explainability and ultimately build trust in AI (McKinsey, 2025).
In this piece, I explore two perspectives; one global, one organisational:
- The Global AI Index by Tortoise Media (UK-based think tank and publisher), which examines which countries are leading in AI and why. It uses a combination of absolute and relative indicators to measure total AI capacity (scale) and AI capacity relative to population and economic size (intensity).
- McKinsey’s Superagency in the Workplace report (January 2025), which explores how leaders and employees can unlock AI’s full potential at work.
Then to close some key questions leaders and team members can ask to continue progressing on their AI journey.
The Global AI Index: who’s leading and why
The Global AI Index (Tortoise Media, 2024) is now in its fifth iteration since launching in 2019.
The index is underpinned by 122 indicators across three pillars (implementation, innovation and investment) collected from 24 different public and private data sources and 83 governments.
Key findings
- United States continues to lead the rankings, extending its lead over China, which retains second place. Together they remain well ahead of all other nations.
- Singapore holds third place, described as Asia’s most dynamic AI hub outside China. It scores strongly on relative measures (such as AI scientists per capita) and has made significant gains on absolute measures, especially in research and investment.
- United Kingdom sits in fourth place, closely followed by France, recognised for leadership in open-source LLM development and government investment.
- South Korea remains sixth, demonstrating strength in applying AI across key industrial sectors.
Other highlights
- Israel is the third most popular destination for private AI funding.
- Canada has the third most comprehensive national AI strategy.
- India enters the top ten for the first time, powered by a deep and diverse AI talent base. Much of this talent migrates overseas, and private investment remains less developed.
- Governments are stepping up AI funding across the board, especially Saudi Arabia, whose public spending commitments significantly outpace those of the US and China.
- Australia ranks 17th of 83 countries, in the first quartile, with its highest rankings in development (7) and research (11).
- Regionally, Japan ranks 11th, Hong Kong 16th, Malaysia 39th and New Zealand 48th.
McKinsey’s Superagency report: empowering people to unlock AI
While country-level benchmarks show how nations compete, organisational benchmarks show how workplaces adapt.
Given AI holds the potential to shift the way people access and use knowledge, McKinsey’s Superagency in the Workplace report argues that the real potential of AI lies not just in technology, but in people empowered to use it.
Key insights
- Superagency emerges when people and AI combine. McKinsey defines “superagency” as the heightened capability that comes when employees are equipped with AI to extend their creativity, judgment and problem-solving, rather than having AI replace them.
- Don’t underestimate employees. Many leaders undervalue how ready their people are to adopt AI. Millennials and Gen Z, who already use AI in their personal lives, are often more confident with the technology than their managers assume.
- Industries moving fastest. Healthcare, technology, media, telecom and agriculture are leading the way. Financial services, energy and materials, consumer goods and retail, and logistics are catching up quickly.
- Where scepticism lingers. Aerospace, defence and the public sector remain more cautious, with employees uncertain about AI’s future role.
Challenges for leaders
To capture AI’s full value, leaders must have the courage to set a bold vision.
The report identifies several common headwinds:
- Leadership alignment: Board and executive teams need shared clarity on AI ambition and pace, as well as how AI will drive value and how risk will be mitigated.
- Cost uncertainty: The ROI and broader benefits of AI projects have not always been clear. This must improve moving forward.
- Workforce planning: Leaders must define which skills will matter in an AI-native workforce and how to reskill at scale.
- Explainability: Black-box AI remains a major barrier to trust. Leaders must demand explainable outputs to ensure adoption.
- Human centricity: More work is needed here. In this survey, fewer than half of technology leaders said they would involve non-technology employees in early AI development.
- Federated governance: Balance local team autonomy with effective risk management and oversight at the organisational level.
What this means for leaders and HR professionals
The pace of AI advancement over the past two years has been extraordinary.
For “AI superagency” to exist, leaders must combine bold vision with practical execution while enabling employees to use AI confidently and responsibly.
Key actions include:
- Invest in infrastructure and ecosystems: Close gaps in compute power, data platforms and commercial maturity.
- Build AI-native cultures: Move from awareness to literacy to embedding AI into daily work, supported by champions who inspire others.
- Prioritise trust and explainability: Integrate benchmarks, testing and governance so employees and customers can trust the systems.
- Empower employees: Recognise that many are more AI-ready than leaders expect. Give them pathways to collaborate, champion adoption and unlock superagency.
Questions to ask
For business leaders
- Is my AI strategy ambitious enough?
- Will AI impact my revenue pipeline, and what am I doing about it?
- What does successful AI adoption look like in my organisation?
- What skills will define an AI-native workforce here?
- What are the skills of my team currently, and what is the capability gap to reskill at scale?
- How many AI experts are needed, and with what skills?
- Does that talent bench even exist? How quickly can I source it?
- Can I remain an attractive employer for in-demand employees post-hiring?
- What are competitors doing with AI that we could adopt, or risk falling behind if we don’t?
- Is my top talent at risk of leaving to join them?
For team members
- What does achieving AI mastery mean for me?
- How do I plan to expand my understanding of AI?
- How can I rethink my own work? Remember that bottom-up innovation often comes from teams.
- Be curious. Get the conversation going with your peers and managers. Share successes and learnings using AI.
Final reflections
Benchmarks like the Global AI Index and McKinsey’s Superagency report remind us that AI is far more than rankings and numbers.
There is still time for organisations to act, but with urgency, alignment and by learning from the lessons already surfaced.
Thoughtful action creates the opportunity for leaders to build workplaces where AI genuinely adds value and significantly augments human potential.
For leaders and HR professionals, the path forward is clear: connect ambition with practical, human-centred execution.
The nations and organisations that succeed will be those that combine infrastructure with talent, explainability with trust, and bold vision with empowered employees.
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Only 1% of companies globally have reached AI maturity (McKinsey, 2025), and in Australia, just 14% have scaled AI across their organisations (Asana, 2025). The opportunity to lead remains wide open.
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References
McKinsey & Company, Superagency in the Workplace: Empowering People to Unlock AI’s Full Potential (January 28, 2025)
