6 Ai trends that are redefining 2024

The progress of AI is expected to be far more than a gradual improvement. It's poised to be a significant transformation, reshaping the technological landscape, legal frameworks, ethical principles, and social interactions. A recent report by Salesforce indicates that 57% of IT leaders believe that AI is a game-changer. Moreover, Gartner predicts that AI will serve as a primary indicator of national power by 2027, driving strategies for the digital economy.

As business leaders strive to take advantage of this era of decision intelligence, the focus for every sector in 2024 will be on harnessing AI’s power for business value: from AI-powered assistants boosting your productivity to machines understanding the world through multiple senses. But this revolution demands responsible handling—open-source models democratize access while regulations like TRiSM ensure ethical, responsible deployments. Let’s delve into the key AI trends in 2024 that are expected to have the most significant impact across industries.

Generative AI remains a dominant force

The potential of generative AI to revolutionize knowledge work across industries and functions has sparked both awe and anticipation. From sales and marketing to customer service and software development, it could automate as much as 60-70% of work tasks, surpassing earlier estimates of 50%. This jump is fueled by AI's improved natural language skills, crucial for activities occupying 25% of work time.

There are two emerging subtrends in generative AI: augmented intelligence and multimodal fusion. Augmented intelligence lets users collaborate with AI, while multimodal AI blends data types for richer AI context and deeper insights. Let's take a closer look at these AI trends:

1. Augmented Intelligence

Augmented Intelligence, or the use of AI and Machine Learning (ML) technologies to enhance human capabilities and decision-making, is often applied in areas where human expertise is crucial, such as healthcare, finance, and data analysis, to assist professionals in making more informed decisions.?

Among the AI trends used in the workplace, the augmented-connected workforce (ACWF) concept is gaining traction. Driven by the need for faster talent development and scalability, ACWF leverages intelligent applications and workforce analytics to provide real-time support and guidance for employee experience, well-being, and skills development.Gartner research indicates that by 2027, 25% of CIOs are expected to implement ACWF initiatives to achieve a 50% reduction in time to competency for critical roles.

2. Multimodal AI

Artificial Intelligence that uses more than one type of data to make more accurate predictions, draw insightful conclusions about a real-world situation is known as multimodal AI. A multimodal AI system uses images, audio, video, speech, text, and traditional numerical data sets to train and learn. Multimodal AI means using many data types in tandem to establish content and interpret context by drawing connections that Data Science, limited to singular data types, often misses.

In Computer Vision, multimodality enables AI to recognize objects and understand their surroundings and context, enhancing identification accuracy. This technology benefits industries with applications in predictive maintenance in manufacturing, personalized healthcare, and driver monitoring in the automotive sector.

Deloitte predicts that in 5+ years, neuroadaptive AI will directly generate outputs based on the user’s brain activity. Contextual awareness, including past actions, emotions, and environment, will empower multimodal models to understand intent more deeply. This will result in AI responses truly adapted to individual personalities.

The time for hesitant exploration is over. The future belongs to those who dare to embrace the potential of generative AI. Businesses should work with an experienced technology partner to get the most out of AI. Being one of only 4 partners in Canada with prestigious Gen AI competency we can help you deliver a tangible results.

Virtual Agents

Virtual agent technology (VAT) is the combination of natural language processing, intelligent search and robotic process automation (RPA) in a single conversational user interface—typically a chatbot—to automate dialogue with end users, provide information, and directly execute actions to meet user requests. Virtual agents, particularly with AI's growing generative capabilities, are becoming a trend as organizations realize the potential for reducing repetitive manual tasks and scaling support operations more efficiently.?

The shift towards smaller, more efficient AI models, which can run locally or at lower costs, further boosts the adoption of virtual agents. This trend allows companies to implement AI-driven customer service without heavy investments in cloud infrastructure, making it more accessible to a wider range of businesses. For instance, a recent Forrester Consulting study estimated that organization could save an average of USD 6.00 per contained conversation using virtual assistant. Improved employee morale also aids employee retention, which has its own financial impact: Gallup research found that the cost replacing an individual employee can range from 50–200% of the departing employee’s annual salary.

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Edge AI

One of Gartner's AI trends predictions for 2024 highlights the rise of edge AI, where processing power migrates closer to data sources. This eliminates dependence on centralized cloud or remote data centers, facilitating faster, local decision-making. No more relying on slow cloud connections; AI algorithms execute directly at the edge, reducing latency and boosting system responsiveness.

For various types of Internet of Things (IoT) applications, edge AI leverages available local computing power. This proves transformative for scenarios demanding real-time decisions, like autonomous vehicles or smart medical devices. Data confidentiality and security also benefit: sensitive information stays local, minimizing unnecessary exposure to external threats.

This convergence of AI and edge computing fosters efficient and responsible solutions. Research anticipates a dramatic shift: Gartner predicts over 55% of deep neural network data analysis to happen at the point of capture in an edge system by 2025, compared to a mere 10% in 2021.?

Open source AI

In 2023, the world saw an explosion of creative possibilities with generative AI, with OpenAI's ChatGPT 3.5 Turbo leading the charge. But now, a new AI trend is emerging: the rise of open-source models. Open-source models empower organizations with transparency, flexibility, and cost-efficiency, fostering wider adoption and democratization of generative AI. While proprietary models still hold a place, we can expect an open-source future: Forrester predicts a staggering 85% of enterprises will integrate open-source AI models by 2025, signifying a shift towards collaborative, accessible AI innovation. These models, unlike their closed-source counterparts, break down barriers to entry and unleash a wave of democratization:

• Accessibility: Open-source LLMs like LLaMA, Vicuna-13B, and Mistral empower individuals and smaller organizations to leverage cutting-edge AI. As a result, previously unimaginable tools are now accessible, fostering widespread innovation and experimentation.
• Democratization of AI training: Techniques like LoRA make fine-tuning accessible, allowing anyone with a computer to participate in AI development. This empowers individuals to contribute to the evolution of LLMs, shaping them for diverse needs and real-world applications.
• User-focused development: Open-source communities are inherently user-driven. Transparency and collaboration ensure LLMs adapt to user needs and priorities, leading to more accessible and impactful applications.

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While still in its early stages, quantum computing is rapidly progressing. Major tech companies and promising startups are actively developing and offering access to quantum computing resources, albeit currently for specialized and often experimental purposes. When combined with AI, quantum computing's potential becomes even more remarkable. The ability to process vast amounts of data at unprecedented speeds could empower AI to perform tasks that are currently beyond its reach, including advanced material design, personalized medicine, and autonomous systems with superior decision-making capabilities.?

Imagine:

1. Accelerating drug discovery: Quantum simulations unlock rapid molecular analysis, leading to faster, more effective drug development.
2. Sharpening climate models: Unprecedented data processing accuracy enhances climate change predictions, empowering us to make informed decisions.
3. Mastering financial markets: Sophisticated analyses enable businesses to navigate the market with unparalleled precision.

Still think AI isn't for your industry? Schedule a call with our expert to discover how we can help you employ AI and ML technologies in your business. Let’s talk

Wrap-up

It's clear that generative AI is no longer a futuristic promise but a dawning reality. Its potential to reshape industries, empower individuals, and redefine entire workflows is no longer hypothetical. AI is expected to drive innovation and progress from augmenting human capabilities to revolutionizing scientific discovery.

Adopting predictive and generative AI goes beyond simply keeping pace with the competition—it opens doors to leadership and groundbreaking innovation. At Dedicatted, we're not just a vendor but your strategic partner in navigating this technological frontier. Leveraging our deep AI and Machine Learning knowledge, we empower your business to transform obstacles into sustainable value, streamlined operations, and enhanced revenue