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CEO Point of View: AI Predictions 2024

Group CEO, Matthieu Courtecuisse, shares his predictions for the AI landscape in 2024.

Matthieu Courtecuisse

Matthieu Courtecuisse

Group CEO, Sia Partners

2024 will be considered as Year #1 for the general adoption of GenAI, in a context of restrictive financial equations.

Here are some trends I expect for this year on the GenAI Market side:

  • Gen AI investments in startups exceeded $25bn in 2023. This peak is likely behind us but will remain very high in 2024, but marked one “AI falling star”.
  • This funding level will help the emergence of LMM vs. LLM. The AI landscape will witness a fierce clash between 'Open Source vs proprietary models' narratives. The financial equation for AI adoption (including IP protection) takes center stage, potentially reshaping OpenAI's competitive advantage by late 2024 and Q1 2025.
  • The Tech winners will be the ones who generate a revenue growth outpacing energy consumption evolution by 5 or 6 times the volume.
  • GenAI's mass adoption in workstations, be it through software packages or opt-in features.
  • The promising start of a GenAI-fueled reinvention of the consumer marketplace.
  • LMMs are gearing up for major strides in conversational voice, speech, videos, and connectivity.
  • Specialized Open Source LLMs, spanning Biology, Chemicals, Logistics and Energy, are anticipated to emerge as high-performance game-changers in 2024.

There will be some threats too...

  • Anticipating the looming threat of at least one impactful GenAI-fueled cybersecurity attack in the near future. Vigilance and robust security measures will be paramount in safeguarding against such risks.
  • Companies face the BYOAI (Bring Your Own AI) threat, with the potential emergence of the first major scandals. The need for stringent AI governance and ethical practices becomes crucial to navigate and mitigate these risks effectively.

...including on the legal front

  • Bracing for a wave of lawsuits related to privacy and IP rights on datasets, potentially causing a slowdown in GenAI deployment. Legal battles may shape the landscape of data rights and usage.
  • The trajectory of the GenAI regulatory framework hinges significantly on the outcome of the US presidential election. Caution is advised for the EU Council, as decisions await both the US election results and EU elections, marking a pivotal period for regulatory approvals and adjustments.

While media attention remains fixated on the Tech giants versus GenAI-native startups, a silent revolution is underway, shaping the AI adoption landscape.


At Sia Partners, we're steering transformative programs in three key areas over the next six months:

1. Business Impact

  • Leveraging our library of 1,000 use cases, we focus on the financial equation from PoC to industrialization. Our technical-agnostic approach, with a preference for OpenSource models, ensures immediate ROI. Frugal engineering frameworks will be a cornerstone.
  • Embracing new corporate norms, restrictions on GPU use will be integrated.

2. GenAI for all Agendas

  • Implementing a change management framework for a workstation revolution, scaling adoption for summary.AI, automated translation, and augmented dashboarding.
  • Initiating significant strides in datasets building, covering data governance, quality, and infrastructure, with comprehensive reporting for CEOs.

3. Building each "CorpGPT"

  • Paving the way for the massive deployment of "CorpGPT", a multi-LLM/multi-cloud infrastructure, aimed at 80% of Fortune 1000 companies. This platform will host numerous internal and external GenAI-fueled applications, shaping the future of corporate AI.
  • SiaGPT exemplifies the ideal approach for companies: establishing a GenAI enterprise platform with a comprehensive privacy policy, ensuring no training on user prompts for employees and stakeholders. It maximizes value through the integration of internal and external datasets, safeguards intellectual property with Open Source Models (LLM and LMM) when feasible, adheres to explainable AI policies, and maintains an efficient multi-cloud and ML/Ops infrastructure.