As 2024 unfolds, a captivating wave of technological transformations is set to redefine the landscape. From smartphones integrating Language Models for seamless translation to the revolutionary impact of Generative AI chatbots on customer service, the tech horizon is ablaze with innovation. Brace yourself for the emergence of AI-generated songs taking the music scene by storm, the debut of an AI-crafted feature film, and the game-changing introduction of Apple Glasses propelling advancements in 3D generation. These 24 predictions, ranging from the democratization of data analytics to the autonomous AI era, promise a year of unparalleled shifts and disruptions, with even political debates and elections poised to be engulfed in the tumultuous embrace of artificial intelligence.
- LLMs Integration in Smartphones: The prolonged absence of significant smartphone innovations has extended the device upgrade cycle. Leading smartphone manufacturers are set to incorporate Language Models (LLMs) into their devices, aiming to prompt customers to upgrade more regularly. An initial application of this integration will be voice-to-voice natural language translation.
- Revolutionizing Customer Service with Chatbots: Enterprises embracing Generative AI chatbots for customer service are witnessing remarkable outcomes. A major enterprise reported a 45% decrease in human-handled customer support requests following the implementation of a Generative AI-based chatbot application. Additionally, a recent study published in the Journal of the American Medical Association (JAMA) revealed that patients preferred AI-generated responses over those from physicians 79% of the time. These early successes will compel enterprises to accelerate their development and implementation of GenAI – based customer service chatbots.
- Widespread Adoption of Co-pilots in Software Development and Maintenance: GitHub conducted a controlled experiment involving 45 developers utilizing GitHub Copilot for a development task, while another 50 developers did not. On average, those using Copilot completed the task 55% faster than their counterparts who did not. Considering the substantial backlog of software development work confronting most enterprises, this notable boost in productivity is poised to ensure the swift adoption of developer co-pilots in 2024.
- Advancements in Open Source LLMs, yet Closed Source Models Maintain Dominance: Open source Language Models (LLMs) like Dolly and Falcon are expected to narrow the gap with their proprietary counterparts in 2024. However, proprietary models such as ChatGPT are anticipated to maintain their lead by the end of the year.
- OpenAI Continues to Lead the LLM Market: In 2024, OpenAI is expected to maintain its position as the foremost producer of Language Models (LLMs), with other competitors, notably Google, making strides to narrow the gap.
- Anticipated Release of the Next ChatGPT Version in 2024: The upcoming iteration of ChatGPT, whether labeled as ChatGPT 4.5 or ChatGPT 5, is set to introduce significant improvements. Expected enhancements include faster processing speeds, real-time information assimilation, specialized knowledge in specific domains, and the incorporation of personalized memory and preferences.
- AI-Generated Songs Take Center Stage: In 2024, expect the emergence of AI-generated songs crafted entirely without human involvement in singing or instrument playing. These innovative compositions are likely to gain widespread popularity and go viral, most likely on Tik-Tok.
- AI-Crafted Feature Film to Debut in 2024: A feature film created entirely through AI technology is set to be released. While it is expected to garner significant attention, it may fall short of achieving blockbuster status at the box office.
- Apple Glasses: A Transformational Catalyst for AI Development: The introduction of Apple Glasses in 2024 is poised to be a transformative force, propelling further advancements in AI, particularly in the realm of 3D generation. This innovation is expected to focus on the creation of separately layered objects within a complete scene, driving the evolution of AI capabilities.
- Shift in Public Cloud Growth: The growth of public clouds, particularly among hyperscalers, is anticipated to slow as companies scrutinize Total Cost of Ownership (TCO) more closely. Nevertheless, a reversal of this trend is expected by the end of the year, driven by heightened interest in AI capabilities hosted on public clouds.
- Databricks Surges Ahead in Market Share: Databricks will gain substantial market share, outpacing its competitors. The appeal of its Datalakehouse architecture, Unity Catalog, and seamless integration with open-source Language Models (LLMs) positions Databricks as the preferred choice for enterprises seeking advanced data solutions.
- Microsoft Fabric Gains Momentum but Falls Short as a Datalakehouse Contender: While Microsoft Fabric is expected to exhibit some momentum, it is not anticipated to emerge as a significant player in the Datalakehouse landscape.
- Democratization of Data Analytics Takes Center Stage in 2024: The democratization of data analytics is set to become a prominent theme. CIOs who have not implemented a robust data strategy within their enterprises will face scrutiny as executives personally explore using natural language for corporate data analysis.
- Auto-Generated, Audience-Specific Political Advertisements on the Horizon:
The rapidly declining costs of creating high quality video will impact political advertising during the 2024 elections. Political video advertisements will be AI-generated, more professional and there will be more variety in those advertisements for each candidate. For example, the upcoming 2024 US Senate race in Virginia will see each candidate creating more geographically specific advertisements tuned to the issues more relevant in each geography. These ads will be run on linear broadcasting by geography and similar AI-generated ads will be used for streaming and web-based advertising (also by geography). Some more advanced campaigns may create semi-personalized video ads that will be inserted in streaming and web-based viewing based on information available about the viewer (when available). For example, a video ad featuring the candidate’s policies regarding tax reductions will be inserted in the stream / web view of a voter segmented as “high income” while a video ad featuring the candidate’s policies regarding better public schools will be inserted in the stream / web view of a voter segmented as “middle income.”
- Integration of Decision-Based Systems into Multi-Modal Models: In 2024, expect the incorporation of decision-based systems into multi-modal models.
- Inclusion of Data in Multi-Modal Models: In 2024, data is set to join voice, text, audio, and video within multi-modal models. Large, public datasets will be curated, tagged, and made accessible through Language Models (LLMs).
- Complete Transactional Autonomy for AI Agents: In 2024, AI agents are expected to manage entire transactions. For instance, instead of merely suggesting travel options based on prompts, GenAI will propose a detailed itinerary, providing options to modify or directly execute the plan. Opting for “execute” would entail the AI agent autonomously booking all components, including flights, hotels, rental cars, and more.
- Emergence of Chief AI Officers: With the evident advantages of adopting Generative AI, enterprises are expected to embrace a comprehensive commitment to AI, leading to the appointment of Chief AI Officers. Unfortunately, like the Chief Data Officers who proceeded them, Chief AI Officers will be only as effective as their level of support from top management.
- Business Process Redesign to Harness AI Capabilities: The redesign of business processes to leverage AI capabilities is poised to become a strategic focus. While initially substituting human activities with AI-based functions may yield benefits, enterprises will realize the full potential of AI when they reach a higher maturity level. This understanding will lead to the realization that the optimal benefits of AI can only be achieved by fundamentally redesigning underlying business processes with AI as a foundational element.
- Evolution of AI Implementation Stages — From Human with AI Co-pilot to Autonomous AI:
In the current marketing landscape, the three stages of AI implementation are unfolding as follows:
- Human with AI Co-pilot Stage: Presently, humans utilize AI as a co-pilot, exemplified by the creation of personalized outreach emails through prompts.
- AI-Agent with Human Co-pilot Stage (2024): In 2024, Generative AI systems are anticipated to automatically generate personalized emails using contact lists and both public and private information about the recipient. The human role involves reviewing, editing, and ultimately sending the email.
- Autonomous AI Stage (Post-2024): Moving beyond 2024, the entire process is expected to become fully automated, eliminating the need for human intervention. This marks the progression to the autonomous AI stage.
- Expansion of Self-Driving Robotaxi Trials Despite Challenges: The trials for self-driving robotaxis are set to expand in the US, persisting even after the incident involving Cruise in San Francisco. Mercedes is expected to introduce Level 3 self-driving cars in Germany. Meanwhile, the progress made by Chinese auto manufacturers will present a dilemma for American politicians and regulators, forcing a balancing act between safety concerns and the international competition surrounding this critical new technology.
- Rising Unemployment Concerns and the Resurgence of Guaranteed Income Discussions:
By the end of the year, the employment repercussions of AI will take center stage in political discourse. Notably, fast food businesses in California will serve as the “tip of the spear” as the state implements a $20/hour minimum wage for fast food workers on April 1. The swift adoption of chatbots for order-taking, followed by mechanized food preparation robots, is expected. Calls for special taxes on AI and/or robots are likely to gain momentum by the end of the year.
- Approaching Data Exhaustion in 2024 and the Challenge of Synthetic Data:
While data exhaustion for training purposes may not fully materialize in 2024, it will draw closer to reality. The capacity to enhance a model by training it on additional data will be hindered as the majority of easily accessible public data has been utilized for model training. Synthetic data generation techniques will be employed to tackle this issue, yet their effectiveness is expected to fall short when compared to the richness of “data in the wild.”
- The 2024 election will demonstrate that the level of AI regulation in the United States is insufficient. Deepfakes will proliferate, although the vast majority will be quickly debunked (much like photoshopped images have been quickly debunked). However, social media sites will be inundated with posts from sophisticated AI bots. These bots will spin and fabricate news to increase polarization and heighten emotions. The social media sites only response will be using AI to fight AI. Legitimate posts will be automatically deleted with cries of partisanship launched at the social media outlets and their managements. Significant and serious US regulation will be forthcoming in the aftermath of the 2024 elections.