Top 4 AI Trends for 2024


The year 2023 marked a significant milestone in the realm of Artificial Intelligence, with technologies such as ChatGPT and Generative AI becoming more interwoven into the fabric of our daily lives and Predictive AI becoming part of mainstream everyday workflows. As we transition into 2024, several key trends are poised to shape the future landscape of AI. What does that mean for progressive organizations, that already have made significant technology investments?

Here’s our pick of top 4 trends that will set the AI tone in the coming year and their implications for an organization.

1. Generative AI comes of age in 2023, but industry use cases driven by private LLMs will take centre stage in 2024

2023 : The year of Generative AI, for consumers - and enterprises

In 2023, generative AI became a buzzword with a lot of hype around ChatGPT and it’s applications to create a new way of generating output and doing work. This has led to expectations among CXOs of a step change in productivity and employees fearing loss of jobs. Think of generative AI powered coding assistants, tutors and concierges  that can complement or replace humans.

2024 : Move to specialized Language Models (private LLMs and SLMs)

In 2024, we will move beyond the hype of generative AI and shift towards specialized LLMs. Organizations will likely invest in creating domain-specific, proprietary LLMs.

For example, BloombergGPT is specially trained on financial data and can help with a wide variety of financial industry tasks using NLP. Similarly Wendao,’s travel industry specific LLM is helping service agents save thousands of hours on a daily basis by providing contextual and relevant answers to customer queries.

Also, while LLMs are becoming experts at generic tasks, companies are focusing on development of light weight Small Language Models (SLMs) tailored for specific functions that demand high-performance outputs.

2. Traditional AI permeates core business functions

AI use cases penetrate deeper within business functions

Traditional Machine Learning models, encompassing Predictive Analytics and Deep Learning have now reached a level of sophistication that heralds their mainstream adoption. Progressive organizations are leveraging these matured models, delving deeper and embedding them further within their operational frameworks. As AI technologies like predictive machine learning, OCR and chatbots have matured, they are also finding deeper applications into core business functions – think of AI embedded use cases surfacing in day to day apps like emails or zero-touch invoice processing.

3. Consolidation of AI initiatives at Enterprise Level

From Siloed AI Pilots to Strategic AI Roadmap

2023 was a year where multiple AI pilots spawned across divisions and functions. CXOs will increasingly realize the need to consolidate these multiple initiatives for efficiency, manageability and compliance. Having a consolidated AI roadmap and reference architecture will enable technology and business leaders to formulate a unified AI vision for the organization by breaking the barrier of siloed AI initiatives. AI consolidation will also be critical to rationalize AI investments and standardize the adoption of AI technologies across the enterprise.

4. Data will continue to be the most important asset

And the Indispensable Fuel for AI

While the AI landscape at organizations evolve, the fundamental need for high-quality data as the lifeblood of AI initiatives remains unchanged. Organizations lagging in this area must invest in their underlying data architectures to harness the full potential of next-gen AI models.


Whether you are an early adopter or an organization looking to experiment with AI, Generative AI holds a lot of promise. Some of the trends outlined above will impact your decision making in 2024. Creating a framework to harness the power of AI will help organizations realize better ROI from their AI initiatives and align them with the strategic AI vision.

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