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What are the AI Trends for 2024
Since the debut of ChatGPT in late 2022 and the introduction of the GPT-4 model in early 2023, the landscape of AI, specifically Generative AI and Large Language Models, has expanded rapidly
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This trend is set to continue in 2024.
These advancements are transforming not just the tech industry but also everyday interactions with AI tools. AI technology has become more accessible and practical, enabling widespread exploration and application beyond tech specialists.
Research indicates that the generative AI market is projected to surge to $38.6 billion by 2028, growing from $3.88 billion in 2023 at a CAGR of nearly 58.3%. This expansion extends beyond software, encompassing the larger market of physical infrastructure for cloud and on-premises support.
Since the debut of ChatGPT in late 2022 and the introduction of the GPT-4 model in early 2023, the landscape of AI, specifically Generative AI and Large Language Models, has expanded rapidly
This trend is set to continue in 2024.
These advancements are transforming not just the tech industry but also everyday interactions with AI tools. AI technology has become more accessible and practical, enabling widespread exploration and application beyond tech specialists.
Research indicates that the generative AI market is projected to surge to $38.6 billion by 2028, growing from $3.88 billion in 2023 at a CAGR of nearly 58.3%. This expansion extends beyond software, encompassing the larger market of physical infrastructure for cloud and on-premises support.
AI-driven business transformation
Usage of multimodal, multi-sensory AI models
AI adaptation in the workplace and augmented working
Data privacy and AI integration
AI legislation and ethical consideration
Changes in industries like retail, finance, healthcare
Funding and growth of AI model providers
1. AI-driven business transformation
- CEO Perspectives on Generative AI: 75% of CEOs believe competitive advantage hinges on having the most advanced generative AI. Currently, 43% of CEOs use generative AI for strategic decisions, and 36% for operational decisions.
- Customized enterprise generative AI models: Businesses are already moving towards customized generative AI models for their specific use cases. It is projected that 30% of outbound marketing messages to be generated synthetically by 2025, leading most organizations to opt for adapting existing AI models to their specific needs. This approach is generally more practical than developing new models from the ground up. Consequently, these tailored models, designed to meet niche requirements, would become more prevalent than large, general-purpose tools.
- AI at the core of business: By 2026, Gartner expects more than 80% of enterprises would have used generative AI and/or deployed generative AI-enabled apps. This could initiate an AI-driven transformation within every business vertical right from sales to operations. Moreover, it would also compel small and medium businesses to tap into intuitive AI platforms which could be a catalyst for the innovative solutions from them.
- Growth in AI-as-a-Service: AI-as-a-Service (AIaaS) is gaining traction, offering businesses a cost-effective way to leverage AI without the need for in-house expertise. The global AIaaS market is forecasted to generate a revenue of USD 55 billion by 2028, growing at a CAGR of 42.6% from 2023 to 2028.
1. AI-driven business transformation
- CEO Perspectives on Generative AI: 75% of CEOs believe competitive advantage hinges on having the most advanced generative AI. Currently, 43% of CEOs use generative AI for strategic decisions, and 36% for operational decisions.
- Customized enterprise generative AI models: Businesses are already moving towards customized generative AI models for their specific use cases. It is projected that 30% of outbound marketing messages to be generated synthetically by 2025, leading most organizations to opt for adapting existing AI models to their specific needs. This approach is generally more practical than developing new models from the ground up. Consequently, these tailored models, designed to meet niche requirements, would become more prevalent than large, general-purpose tools.
- AI at the core of business: By 2026, Gartner expects more than 80% of enterprises would have used generative AI and/or deployed generative AI-enabled apps. This could initiate an AI-driven transformation within every business vertical right from sales to operations. Moreover, it would also compel small and medium businesses to tap into intuitive AI platforms which could be a catalyst for the innovative solutions from them.
- Growth in AI-as-a-Service: AI-as-a-Service (AIaaS) is gaining traction, offering businesses a cost-effective way to leverage AI without the need for in-house expertise. The global AIaaS market is forecasted to generate a revenue of USD 55 billion by 2028, growing at a CAGR of 42.6% from 2023 to 2028.
2. Usage of multimodal, multisensory AI models
- Multilayered content generation: Multimodal AI model provides output with a combination of text, image, audio, etc. This leads to multilayered content generation and multisensory experiences. With this, we are moving towards a trend of next-generation generative AI that goes beyond chatbots and meme generators.
This includes using a harmonized blend of AI generators like Runway, Midjourney, DALL-E 3, etc. to create complex narratives, musical compositions, and possibly co-authoring bestselling novels.
- Move to personal devices: Generative AI, primarily cloud-based in 2023, is expected to transition to personal devices due to privacy, latency, and cost concerns. Qualcomm Technologies’ Senior VP & GM of Technology Planning & Edge Solutions, Durga Malladi, foresees personal devices like smartphones, PCs, and IoT devices becoming hubs for multi-modal generative AI models. This shift aims to enhance privacy-focused, personalized AI experiences and reduce cloud costs for developers.
2. Usage of multimodal, multisensory AI models
- Multilayered content generation: Multimodal AI model provides output with a combination of text, image, audio, etc. This leads to multilayered content generation and multisensory experiences. With this, we are moving towards a trend of next-generation generative AI that goes beyond chatbots and meme generators.
This includes using a harmonized blend of AI generators like Runway, Midjourney, DALL-E 3, etc. to create complex narratives, musical compositions, and possibly co-authoring bestselling novels.
- Move to personal devices: Generative AI, primarily cloud-based in 2023, is expected to transition to personal devices due to privacy, latency, and cost concerns. Qualcomm Technologies’ Senior VP & GM of Technology Planning & Edge Solutions, Durga Malladi, foresees personal devices like smartphones, PCs, and IoT devices becoming hubs for multi-modal generative AI models. This shift aims to enhance privacy-focused, personalized AI experiences and reduce cloud costs for developers.
3. Adaptation of AI in the workforce and the rise of augmented working
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- Augmented working: Research indicates that AI's integration into the workforce significantly boosts productivity and job satisfaction: 72% of businesses extensively using AI report high productivity, compared to 55% of limited AI users. Additionally, 59% of AI users experience greater job satisfaction. This trend highlights AI's positive impact on efficiency and employee morale, shaping the future workforce dynamics.
- AI as a co-worker: There's an anticipated increase in AI as a co-worker in 2024. AI bots will take on routine tasks, allowing humans to focus on strategic work. Currently, 87% of executives expect job roles to be augmented, not replaced, by generative AI.
- Workforce impact and reskilling: The impact of AI on job roles is expected to deepen. CEOs estimate that 40% of their workforce will need reskilling over the next three years. A majority of government leaders anticipate spending more on AI and automation than on human talent within five years.
- Smarter customer service: By 2024, Gartner anticipates 100 million requests for customer service will be raised by smart products. and by 2026, 20% of inbound customer service contact volume will come from machine customers.
3. Adaptation of AI in the workforce and the rise of augmented working
- Augmented working: Research indicates that AI's integration into the workforce significantly boosts productivity and job satisfaction: 72% of businesses extensively using AI report high productivity, compared to 55% of limited AI users. Additionally, 59% of AI users experience greater job satisfaction. This trend highlights AI's positive impact on efficiency and employee morale, shaping the future workforce dynamics.
- AI as a co-worker: There's an anticipated increase in AI as a co-worker in 2024. AI bots will take on routine tasks, allowing humans to focus on strategic work. Currently, 87% of CEOs expect job roles to be augmented, not replaced, by generative AI.
- Workforce impact and reskilling: The impact of AI on job roles is expected to deepen. CEOs estimate that 40% of their workforce will need reskilling over the next three years. A majority of government leaders anticipate spending more on AI and automation than on human talent within five years.
- Smarter customer service: By 2024, Gartner anticipates 100 million requests for customer service will be raised by smart products. and by 2026, 20% of inbound customer service contact volume will come from machine customers.
CEOs feeling pressure from stakeholders to accelerate AI adoptions.
60%
Board members
64%
Investors
55%
Employees
55%
Media or Press
4. Data privacy and AI integration
- Data privacy as a strategic asset: According to the report – Forrester 2024 Predictions for Cybersecurity, Risk, And Privacy – there’s a growing concern that insecure AI-generated code could potentially lead to at least 3 data breaches in the coming years. These risks stem from both the security vulnerabilities in the code itself as well as the flaws in AI-recommended dependencies.
Given this fact, in 2024 data privacy wouldn’t be just a compliance requirement; it might become a necessary strategic asset. Companies that will prioritize robust data privacy strategies will not only win consumer trust but also gain a competitive edge. This shift is crucial in an era when a single data breach can severely tarnish a brand's reputation.
- Insurance covers: With data privacy, simultaneously, there’s a rising interest in insurance covers for generative AI and AI models that may fail. Similar to the rise in cybersecurity insurance, this new trend reflects the growing need for protection against AI failures. Avivah Litan, an analyst at Gartner, speculates that over 50% of large enterprises are likely to invest in such AI insurance policies once available. This trend is a logical step, considering the increasing reliance on and risks associated with AI technologies.
- Increasing cybersecurity budgets: The growing complexity of cyber threats has necessitated a significant increase in cybersecurity budgets. In 2023, there was a notable rise of 51% in these budgets compared to 2021. Looking ahead, these budgets are expected to climb another 43% by 2025. This trend highlights the evolving nature of cybersecurity, transitioning from a purely technical requirement to a key strategic differentiator for organizations.
- Zero trust environments: With more advanced threats, there's an emphasis on zero trust environments, requiring authentication and verification for every exchange of value. This approach is necessary to protect data across dynamic networks and diffuse boundaries. It is predicted that about 10% of the large enterprises will opt for a mature and zero-trust program by 2026. In comparison, this number stood at just 1% at the beginning of 2023.
4. Data privacy and AI integration
- Data privacy as a strategic asset: According to the report – Forrester 2024 Predictions for Cybersecurity, Risk, And Privacy – there’s a growing concern that insecure AI-generated code could potentially lead to at least 3 data breaches in the coming years. These risks stem from both the security vulnerabilities in the code itself as well as the flaws in AI-recommended dependencies.
Given this fact, in 2024 data privacy wouldn’t be just a compliance requirement; it might become a necessary strategic asset. Companies that will prioritize robust data privacy strategies will not only win consumer trust but also gain a competitive edge. This shift is crucial in an era when a single data breach can severely tarnish a brand's reputation.
- Insurance covers: With data privacy, simultaneously, there’s a rising interest in insurance covers for generative AI and AI models that may fail. Similar to the rise in cybersecurity insurance, this new trend reflects the growing need for protection against AI failures. Avivah Litan, an analyst at Gartner, speculates that over 50% of large enterprises are likely to invest in such AI insurance policies once available. This trend is a logical step, considering the increasing reliance on and risks associated with AI technologies.
- Increasing cybersecurity budgets: The growing complexity of cyber threats has necessitated a significant increase in cybersecurity budgets. In 2023, there was a notable rise of 51% in these budgets compared to 2021. Looking ahead, these budgets are expected to climb another 43% by 2025. This trend highlights the evolving nature of cybersecurity, transitioning from a purely technical requirement to a key strategic differentiator for organizations.
- Zero trust environments: With more advanced threats, there's an emphasis on zero trust environments, requiring authentication and verification for every exchange of value. This approach is necessary to protect data across dynamic networks and diffuse boundaries. It is predicted that about 10% of the large enterprises will opt for a mature and zero-trust program by 2026. In comparison, this number stood at just 1% at the beginning of 2023.
5. AI legislation and ethical consideration
- Ethical AI: With over 75% of consumers concerned about the usage of AI in businesses, the demand for transparent and ethical AI practices is gaining momentum. This trend indicates a need for greater transparency and ethical standards in AI, essential for building trust between businesses and their customers. In 2024, expect a rise in AI ethics education and a stronger focus on ethical AI research and development, aiming to tackle ethical challenges, bias in algorithms, and enforce strict accountability.
- Responsible AI is being prioritized: Responsible AI is increasingly becoming a focal point for both governments and technology providers. Regions like the EU, the UK, Canada, and the US are actively engaged in developing or implementing regulations specific to artificial intelligence. This shift towards regulation highlights a growing awareness of the need for ethical and accountable AI practices.
Moreover, with major technology companies aligning with this trend, signifies a move towards a future where AI is used responsibly and ethically, balancing innovation with societal and moral considerations. For instance, 30% of the organizations that are implementing or exploring generative AI have stringent guidelines for the usage of AI systems – and we might see the number rising in the coming years.
5. AI legislation and ethical consideration
- Ethical AI: With over 75% of consumers concerned about the usage of AI in businesses, the demand for transparent and ethical AI practices is gaining momentum. This trend indicates a need for greater transparency and ethical standards in AI, essential for building trust between businesses and their customers. In 2024, expect a rise in AI ethics education and a stronger focus on ethical AI research and development, aiming to tackle ethical challenges, bias in algorithms, and enforce strict accountability.
- Responsible AI is being prioritized: Responsible AI is increasingly becoming a focal point for both governments and technology providers. Regions like the EU, the UK, Canada, and the US are actively engaged in developing or implementing regulations specific to artificial intelligence. This shift towards regulation highlights a growing awareness of the need for ethical and accountable AI practices.
Moreover, with major technology companies aligning with this trend, signifies a move towards a future where AI is used responsibly and ethically, balancing innovation with societal and moral considerations. For instance, 30% of the organizations that are implementing or exploring generative AI have stringent guidelines for the usage of AI systems – and we might see the number rising in the coming years.
6. Changes in industries like retail, finance, healthcare, etc.
- AI-driven PC market transformation: A significant shift in the PC market is expected in 2024, driven by AI advancements. Morgan Stanley predicts 40% of laptops will be due for replacement in 2024, increasing to 65% by 2025. Qualcomm Technologies’ Senior VP and GM of Compute and Gaming, Kedar Kondap, anticipates a "super cycle" in the PC market, marking a revolution in AI PCs.
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- Financial services and AI adoption: The financial services industry is set to increasingly adopt generative AI, tailored to meet specific sector needs, including compliance with regulatory standards. Despite initial hesitancy, particularly among buy-side investors, a growing number of investment managers (22%) recognize the expanding role of AI in their investment processes, signaling a significant shift towards AI integration in financial strategies.
- AI in healthcare: AI is expected to play a pivotal role in streamlining administration, diagnosis, treatment, and patient care in 2024. AI can potentially save the US healthcare system an estimated $360 billion annually over the next five years. Moreover, global AI in healthcare is believed to grow at a CAGR of 47.6% from USD 14.6 billion in 2023 to USD 102.7 billion in 2028.
6. Changes in industries like retail, finance, healthcare, etc.
- AI-driven PC market transformation: A significant shift in the PC market is expected in 2024, driven by AI advancements. Morgan Stanley predicts 40% of laptops will be due for replacement in 2024, increasing to 65% by 2025. Qualcomm Technologies’ Senior VP and GM of Compute and Gaming, Kedar Kondap, anticipates a "super cycle" in the PC market, marking a revolution in AI PCs.
- Financial services and AI adoption: The financial services industry is set to increasingly adopt generative AI, tailored to meet specific sector needs, including compliance with regulatory standards. Despite initial hesitancy, particularly among buy-side investors, a growing number of investment managers (22%) recognize the expanding role of AI in their investment processes, signaling a significant shift towards AI integration in financial strategies.
- AI in healthcare: AI is expected to play a pivotal role in streamlining administration, diagnosis, treatment, and patient care in 2024. AI can potentially save the US healthcare system an estimated $360 billion annually over the next five years. Moreover, global AI in healthcare is believed to grow at a CAGR of 47.6% from USD 14.6 billion in 2023 to USD 102.7 billion in 2028.
7. Funding and growth of AI model providers
In 2023, there has been an increase in investments in foundational AI model providers signaling strong investor confidence in AI's transformative potential.
While data for individual years within the 2020-2023 timeframe is not readily available, we do know that in 2023 alone, AI startups garnered a record-breaking $50 billion in funding, according to data from AltIndex.com.
The upward financial trend reflects a period of rapid growth and innovation in generative AI, emphasizing its significant future prospects.
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- xAI: xAI launched in July 2023 has seen explosive progress in a short time. They've rapidly iterated on their Grok series of models, culminating in the Grok-1.5V with image understanding. This rapid advancement is fueled by their recent Series B funding round of $6 billion, with backing from some major investors like Valor Equity Partners, Vy Capital, Andreessen Horowitz, Sequoia Capital, Fidelity Management & Research Company, Prince Alwaleed Bin Talal and Kingdom Holding.
- Anthropic: Anthropic, known for competing with OpenAI in building AI foundation models, is already backed up by giants like Google and Amazon, and is valued at $4.1 billion in the year 2023. In December 2023, Anthropic was in talks with Menlo Ventures to raise funding of $750 million. With this round, Anthropic would potentially be valued at $18.4 billion.
- AI21 Labs: AI21 Labs, in November 2023, completed a $208 million Series C funding round, raising its total capital to $283 million at a valuation of $1.4 billion.
- Aleph Alpha: Aleph Alpha, a German-based AI startup, has raised over $500 million in a Series B funding round in November 2023. They focus on supplying AI solutions to enterprise and government customers, emphasizing data privacy, security, and transparency, especially in regulated industries like healthcare and finance.
- Hugging Face: Hugging Face has been valued at $4.5 billion after its funding round in August 2023, after securing $235 million. This funding round was backed by technology heavyweights like Salesforce, Alphabet's Google, and Nvidia.
- Cohere AI: In June 2023, Cohere AI raised $270 million as part of its Series C round, bringing its total funding to $445 million and valuing the company at over $2.1 billion.
7. Funding and growth of AI model providers
In 2023, there has been an increase in investments in foundational AI model providers signaling strong investor confidence in AI's transformative potential.
While data for individual years within the 2020-2023 timeframe is not readily available, we do know that in 2023 alone, AI startups garnered a record-breaking $50 billion in funding, according to data from AltIndex.com.
The upward financial trend reflects a period of rapid growth and innovation in generative AI, emphasizing its significant future prospects.
- Anthropic: Anthropic, known for competing with OpenAI in building AI foundation models, is already backed up by giants like Google and Amazon, and is valued at $4.1 billion in the year 2023. In December 2023, Anthropic was in talks with Menlo Ventures to raise funding of $750 million. With this round, Anthropic would potentially be valued at $18.4 billion.
- AI21 Labs: AI21 Labs, in November 2023, completed a $208 million Series C funding round, raising its total capital to $283 million at a valuation of $1.4 billion.
- Aleph Alpha: Aleph Alpha, a German-based AI startup, has raised over $500 million in a Series B funding round in November 2023. They focus on supplying AI solutions to enterprise and government customers, emphasizing data privacy, security, and transparency, especially in regulated industries like healthcare and finance.
- Hugging Face: Hugging Face has been valued at $4.5 billion after its funding round in August 2023, after securing $235 million. This funding round was backed by technology heavyweights like Salesforce, Alphabet's Google, and Nvidia.
- Cohere AI: In June 2023, Cohere AI raised $270 million as part of its Series C round, bringing its total funding to $445 million and valuing the company at over $2.1 billion.
