Boston Consulting Group: 40% of Saudi Organizations Now Qualify as AI Leaders 

A general view of Riyadh, Saudi Arabia. (SPA)
A general view of Riyadh, Saudi Arabia. (SPA)
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Boston Consulting Group: 40% of Saudi Organizations Now Qualify as AI Leaders 

A general view of Riyadh, Saudi Arabia. (SPA)
A general view of Riyadh, Saudi Arabia. (SPA)

Saudi Arabia exhibits remarkable AI advancement, with 40% of organizations now qualifying as AI Leaders according to a comprehensive new study by Boston Consulting Group. The report, "Unlocking Potential: How GCC Organizations Can Convert AI Momentum into Value at Scale," revealed that Saudi organizations are successfully matching global benchmarks while demonstrating exceptional scale in AI implementation across the Kingdom's diverse economic landscape.

The study, which surveyed 200 C-suite executives and assessed 41 digital and AI capabilities across seven industries, showed that 35% of Saudi organizations have reached the critical "Scaling" AI maturity stage, reflecting rapid expansion beyond experimental phases toward comprehensive enterprise deployment.

With an average AI maturity score of 43, the report demonstrated Saudi Arabia’s solid progress in AI sophistication, while also indicating a significant opportunity for continued advancement for the 27% of organizations that remain in the "Stagnating" category.

"Saudi Arabia's progress in AI adoption reflects the Kingdom's commitment to technological transformation at unprecedented scale," said Rami Mourtada, Partner & Director, Digital Transformation at Boston Consulting Group.

"AI leaders in Saudi Arabia are uniquely positioned to leverage the Kingdom's commitment to and sizable investments in building globally competitive AI infrastructures to drive substantial business impact across multiple industries simultaneously," he added.

"The key for Saudi organizations moving forward lies in adopting systematic approaches to AI value creation through comprehensive strategies that address their local challenges while nurturing a global outlook," he went on to say.

Across the broader Gulf Cooperation Council (GCC) region, the report demonstrated remarkable progress in closing the AI adoption gap with global markets. According to the report, 39% of all GCC organizations now qualify as AI Leaders, compared to the global average of 40%, representing a fundamental transformation in how regional businesses approach artificial intelligence.

The GCC region demonstrates exceptional AI leadership, with its Public Sector achieving the highest AI maturity levels globally across all surveyed markets. While TMT continues to lead in AI maturity within the GCC, there is rapid advancement occurring in other critical sectors including Financial Institutions, Health Care, Industrial Goods, and Travel, Cities, and Infrastructure, highlighting the region's broad-based AI transformation, said the report.

The financial impact of AI leadership proves substantial, with AI Leaders across the GCC delivering up to 1.7 times higher total shareholder returns and 1.5 times higher EBIT margins compared to AI Laggards. This performance differential underscores the critical importance of moving beyond pilot programs toward scaled implementation.

This success is directly linked to higher AI investment levels - AI Leaders are dedicating 6.2% of their IT budgets to AI in 2025 compared to only 4.2% by Laggards. As AI budgets continue to grow, the value generated by AI Leaders is expected to be 3-5x higher by 2028, not only amplifying their competitive advantage but also significantly widening the performance gap between Leaders and Laggards.

While the GCC has demonstrated advanced digital maturity in recent years, AI maturity has surged by 8 points between 2024 and 2025, now trailing overall digital maturity by just 2 points.

The study revealed that successful AI Leaders distinguish themselves through five critical strategic moves: pursuing multi-year strategic ambitions with 2.5 times more leadership engagement than laggards, fundamentally reshaping business processes rather than simply deploying off-the-shelf solutions, implementing AI-first operating models with robust governance frameworks, securing and upskilling talent at 1.8 times the rate of competitors, and building fit-for-purpose technology architectures that reduce adoption challenges by 15%.

Looking toward frontier technologies, 38% of GCC organizations are already experimenting with agentic AI, positioning the region competitively against the global average of 46%. The value generated from agentic AI initiatives, currently at 17%, is projected to double to 29% by 2028, driven by continued experimentation and strategic deployment.

Despite this strong momentum, GCC organizations continue to face barriers to AI adoption, with AI Laggards 18% more likely than AI Leaders to encounter people, organization, process challenges stemming from limited cross-functional collaboration on AI, unclear AI value measurement, misalignment with enterprise strategy, or lack of leadership commitment.

AI Laggards are also 17% more likely to face challenges in algorithm implementation, especially around limited access to high-quality data, and 10% more likely to encounter technology constraints, such as security risks and RAI implementation, in addition to a general constraint in the availability of local GPUs, further increasing burden on organizations.

"AI laggards are more likely to face people, organization, and process barriers, often compounded by difficulties in creating AI-focused roles and attracting scarce talent at competitive market rates. Infrastructure constraints, including limited access to GPUs, add further pressure," said Semyon Schetinin, Managing Director & Partner at Boston Consulting Group.

"The next phase of value creation will depend on multi-year strategic ambitions that address these realities head-on. This includes building robust AI training and upskilling pipelines, evolving private-sector talent sourcing strategies, and strengthening public-private sector collaboration to improve access to top technology and enable sustained, scalable AI impact," he stressed.

The report emphasized that sustained AI leadership requires continued focus on executive engagement, comprehensive talent development, responsible AI governance, and strategic alignment between AI initiatives and broader business objectives. As Saudi organizations continue their AI transformation journey, their ability to deploy AI at scale across sectors, supported by strong public- and private-sector advancement, further strengthens their capacity to translate AI adoption into meaningful value creation.



China's Tencent Says AI Agents Showed Unintended Browsing Behavior

FILE PHOTO: The Tencent logo at the company's headquarters during a government‑organised media trip in Shenzhen, Guangdong province, China, April 17, 2026.  REUTERS/Go Nakamura/File Photo
FILE PHOTO: The Tencent logo at the company's headquarters during a government‑organised media trip in Shenzhen, Guangdong province, China, April 17, 2026. REUTERS/Go Nakamura/File Photo
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China's Tencent Says AI Agents Showed Unintended Browsing Behavior

FILE PHOTO: The Tencent logo at the company's headquarters during a government‑organised media trip in Shenzhen, Guangdong province, China, April 17, 2026.  REUTERS/Go Nakamura/File Photo
FILE PHOTO: The Tencent logo at the company's headquarters during a government‑organised media trip in Shenzhen, Guangdong province, China, April 17, 2026. REUTERS/Go Nakamura/File Photo

Tencent said on Friday that AI agents used to evaluate third-party models displayed web-browsing behavior not intended by the tech giant, in what appears to be the first known incident of rogue agent actions acknowledged by a major Chinese company.

The statement followed a report by AI-safety research group Swarmchasers on Wednesday, which said "rogue" agents running on infrastructure it linked to Tencent Cloud made repeated attempts between September 28 and October 8 to retrieve information from Alibaba's Amap, China's equivalent to Google Maps.

Tencent Hunyuan, the company's artificial ⁠intelligence unit, said in ⁠a post on X that the activity did not originate from its Hunyuan models. Its review found no evidence of deliberate targeting or coordination, Reuters quoted it as saying.

The Swarmchasers researchers said the agents sought information such as the commonly used entrances at Chinese parks, museums and zoos.

The actions are not as egregious as those disclosed by US AI companies which include the hack of ⁠open-source platform Hugging Face by an OpenAI agent and the lodging of a fake homicide tip by an Anthropic agent.

But the disclosure underscores research that shows Chinese AI agents can also misrepresent their identity, conceal failures and try to circumvent testing controls.

Tencent said it took the findings very seriously and was strengthening network access controls and agent monitoring.

Hunyuan is one of China's leading AI model developers, competing with in-house teams at rivals such as Alibaba and ByteDance. ByteDance this week announced the creation of a new unit focused on AI model and agent safety.

Swarmchasers said it used the ⁠word "rogue" to ⁠describe agents taking actions outside their intended scope or completing a task in unintended ways.

After routine automated requests were blocked, the agents tried other methods, including public web tools that could open pages and run code, routing requests through other websites and using Amap keys and security codes found in publicly available software code.

Swarmchasers said it found no evidence that the agents breached Amap's main anti-bot safeguards. Most of the 2,818 attempts it recorded either failed or returned anti-bot pages, login screens or blank results.

Some requests returned information through cached pages and intermediary services, including data on visitor arrivals at Chengdu Zoo, Swarmchasers said. The researchers said they could not determine whether an agent read the result or completed its task.


Anthropic Co-founder Renews Call for Robust Regulation of Frontier AI

AI Research Company Anthropic's Co-Founder and Head of Public Benefit Jack Clark speaks during the Artificial Intelligence and the Global Economy From Risk to Opportunity event of the 2026 Annual Meetings of the IMF and the World Bank Group in Bangkok, Thailand, 16 October 2026. EPA/RUNGROJ YONGRIT
AI Research Company Anthropic's Co-Founder and Head of Public Benefit Jack Clark speaks during the Artificial Intelligence and the Global Economy From Risk to Opportunity event of the 2026 Annual Meetings of the IMF and the World Bank Group in Bangkok, Thailand, 16 October 2026. EPA/RUNGROJ YONGRIT
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Anthropic Co-founder Renews Call for Robust Regulation of Frontier AI

AI Research Company Anthropic's Co-Founder and Head of Public Benefit Jack Clark speaks during the Artificial Intelligence and the Global Economy From Risk to Opportunity event of the 2026 Annual Meetings of the IMF and the World Bank Group in Bangkok, Thailand, 16 October 2026. EPA/RUNGROJ YONGRIT
AI Research Company Anthropic's Co-Founder and Head of Public Benefit Jack Clark speaks during the Artificial Intelligence and the Global Economy From Risk to Opportunity event of the 2026 Annual Meetings of the IMF and the World Bank Group in Bangkok, Thailand, 16 October 2026. EPA/RUNGROJ YONGRIT

Anthropic co-founder Jack Clark renewed calls on Friday for regulating artificial intelligence, saying that allowing companies to continue to operate without robust legislation was like letting a race car loose on the streets at night without brakes.

"It's remarkable to me that the toys I buy for my children are regulated more than the literal super intelligence I work on at my day job," he told an event at the IMF-World Bank's Annual Meetings in Bangkok.

Clark said that US President Donald Trump, whose administration has called for the industry to police itself, was against the idea of regulation but that China was not, said AFP.

"I think it's Formula One at night without maybe brakes in the cars," he said.

He said the lack of clarity around the will for regulation meant "the Formula One car is roaring round and nobody seems to want to put up a guardrail?"

At an industry summit in Dublin on Wednesday, calls to prioritize safety in the development of powerful AI technology dominated the conversation.

Concerns about AI guardrails have soared after models developed by OpenAI and Anthropic were involved in security incidents during testing, piling on pressure to regulate the technology.

A recent Anthropic report suggested small AI models may be only months away from behaving like computer worms, copying themselves from one internet-connected device to the next.

Anthropic has been among those companies calling for governments to step in, even suggesting international coordination to slow down the whole industry -- including Chinese rivals.

That initiative has so far failed to materialize, with companies involved in a hyper-competitive race to attract as much investment as possible.


Meta Releases Open-Weight Muse Spark Model for Coding, Agentic Tasks

The logo of Meta is seen at the entrance of the company's temporary stand ahead of the World Economic Forum (WEF) in Davos, Switzerland January 18, 2025. (Reuters)
The logo of Meta is seen at the entrance of the company's temporary stand ahead of the World Economic Forum (WEF) in Davos, Switzerland January 18, 2025. (Reuters)
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Meta Releases Open-Weight Muse Spark Model for Coding, Agentic Tasks

The logo of Meta is seen at the entrance of the company's temporary stand ahead of the World Economic Forum (WEF) in Davos, Switzerland January 18, 2025. (Reuters)
The logo of Meta is seen at the entrance of the company's temporary stand ahead of the World Economic Forum (WEF) in Davos, Switzerland January 18, 2025. (Reuters)

Meta ‌Platforms on Thursday released an open-weight version of its Muse Spark artificial intelligence model for coding and AI agents, expanding developers' ability to download and adapt the technology.

Open-weight models make trained parameters available for developers to modify, unlike proprietary models ‌that remain under ‌their creators' control. ‌They ⁠can offer businesses ⁠a lower-cost alternative to closed systems.

Meta said Muse Spark has 816 billion total parameters, with 42 billion active at a time, and ⁠can handle a context window ‌of up ‌to 1 million tokens.

The ‌model can run locally on ‌two Apple M5 Ultra Mac Studio computers and is also available through some API providers.

CEO ‌Mark Zuckerberg has argued that advanced AI should ⁠not be ⁠concentrated among a small number of companies.

While open-weight models can give companies greater control over their data, they can require significant computing resources and technical expertise to operate at scale.

In August, Meta released Muse Glimmer, a smaller open-weight model.