In 2023, an unexpected development took place: the global introduction of generative AI technology. With this newfound knowledge, businesses are racing to capitalize on it while also addressing its potential drawbacks. This has created significant interest in observing the evolution of generative artificial intelligence throughout 2024, leading to numerous predictions on the subject.

1. Leaner language models

In 2024, language models will be as powerful as they are now, but they will be much simpler, using only one-tenth of the complexity.

These models will also perform well with just a fraction of the usual data, making them more practical. Transformer, the current go-to architecture, will no longer be the top choice, especially for simpler models. Instead, systems capable of handling multiple types of information will become more common.

Reinforcement learning and direct preference optimization (RL/DPO) will become widely used in open-source models, and we'll discover new approaches beyond traditional methods for model alignment. The boundaries between pre-training and alignment strategies will become less distinct, and we won't rely solely on predicting the next word in large text collections.

2. The rise of secure AI

AI development will accelerate significantly in 2024, reaching a point by year-end where companies can confidently use it for important business decisions.

Nonetheless, there will be opportunities along the way. After this rapid growth, many AI companies will adapt and thrive, benefiting from a heightened focus on safeguarding data privacy, security, and safety.

Therefore, 2024 will be marked as the year when secure and trustworthy AI companies will thrive. The surge in AI investment and innovation will bring consolidation and speed up advancements, resulting in standout winners across various industries.

3. Gen AI goes mainstream

Gen AI will become widely accessible and integrated into various applications.

It might sound surprising that such a powerful technology could become commonplace so quickly, but in 2024, this process will begin. Foundational models like LLMs are already getting easier to train and customize, and enterprises will start embedding generative AI into more of their applications this year.

4. Shift to local Gen AI

In 2024, there will be a swift transition from cloud-based Gen AI to local Gen AI.

Most startups can't afford the high costs of cloud providers, but the rise of local generative AI is changing this landscape. With local Gen AI, you'll have full control over your RAG stack and access permissions, safeguarding your proprietary data. The shift from centralized, API-based to local LLMs will happen rapidly, with successful solutions quickly gaining popularity.

5. Beyond gen AI adoption

Simply embracing Gen AI won't be sufficient for SaaS companies to progress significantly in 2024.

Startups aiming to become the Gen AI version of specific categories will face challenges as established software platforms develop competing products. Customers will prefer consolidating vendors rather than seeking new ones. Startups must innovate their business or acquire valuable, unique datasets. Startups that can achieve both of these goals have the potential to become enduring companies.

6. Expanding Gen AI application

In 2024, software companies will discover new ways to utilize Gen AI.

This technology will evolve from being a cost-saving tool to becoming an integral part of company operations. It will bring advantages like revolutionizing supply chain processes and providing more personalized products to customers.

Currently, organizations fund generative AI projects from various departmental budgets, mainly from data science and analytics. There will be a shift in how organizations allocate resources, with Gen AI having its dedicated budget and a leader responsible for integration. However, achieving full integration, given the need for training and customization, will be a gradual process spanning several years, not limited to 2024 alone.

7. Pragmatic Gen AI adoption

Technology leaders will aim for a more grounded approach to Gen AI in 2024.

The adoption of AI is expected to continue accelerating, especially for CX (customer experience) applications. However, business leaders will increasingly understand that generative AI is not a one-size-fits-all solution.

Its true power lies in specific use cases, often in combination with other AI techniques tailored to meet specific business needs. Organizations that strike the right balance between AI speed and adaptability on one hand and responsibility and security on the other will be best positioned to deliver maximum value to their customers and improve their bottom line.

8. The ethical role of casual AI

2024 will be the year for practical AI in SaaS, shifting the focus from a rush of generative AI to more strategic innovation.

Predictive analytics will offer users advanced insights, ever-smarter deep learning will tackle complex challenges, and causal AI will play a crucial role in explaining decisions and ensuring AI effectiveness, making it an ethical champion.

Catalysts for thriving business success

To position themselves for thriving success in the dynamic landscape of 2024 and beyond, businesses should give careful consideration to the following strategic recommendations:

• Anticipate simpler yet potent AI models.
• Utilize models that require less data, enhancing practicality.
• Consider innovative AI architectures and techniques.
• Recognize AI's accelerated development for crucial business decisions.
• Leverage opportunities amid growth, emphasizing data security.
• Establish your brand as a trustworthy AI provider.
• Embrace Gen AI's growing accessibility and application diversity.
• Evaluate transitioning from cloud-based to local AI solutions.
• Benefit from greater control and data protection.
• Understand adopting AI alone may not suffice.
• Innovate business models or acquire unique datasets.
• Prepare for AI's deeper integration into business operations.