Astronaut loading animation Circular loading bar

Try : Insurtech, Application Development

AgriTech(1)

Augmented Reality(20)

Clean Tech(5)

Customer Journey(12)

Design(36)

Solar Industry(6)

User Experience(56)

Edtech(10)

Events(34)

HR Tech(2)

Interviews(10)

Life@mantra(11)

Logistics(5)

Strategy(17)

Testing(9)

Android(47)

Backend(30)

Dev Ops(7)

Enterprise Solution(27)

Technology Modernization(2)

Frontend(28)

iOS(43)

Javascript(15)

AI in Insurance(35)

Insurtech(63)

Product Innovation(49)

Solutions(19)

E-health(10)

HealthTech(22)

mHealth(5)

Telehealth Care(4)

Telemedicine(5)

Artificial Intelligence(132)

Bitcoin(8)

Blockchain(19)

Cognitive Computing(7)

Computer Vision(8)

Data Science(17)

FinTech(50)

Banking(7)

Intelligent Automation(26)

Machine Learning(47)

Natural Language Processing(14)

expand Menu Filters

Gen AI’s Next Leap: Predicting the Future of Artificial Intelligence in 2024 and Beyond

In recent years, artificial intelligence has transformed from a futuristic concept into a dynamic and influential force across various industries. A striking statistic from Deloitte’s Managing Director, Manoj Suvarna, highlights this evolution: Generative AI (GenAI) has become more mainstream than ever before, reshaping traditional business workflows and introducing novel content creation methods​​. This article delves into the current landscape and Gen AI’s next leap, exploring how it’s poised to continue revolutionizing the way we live and work.

Rise of Gen AI

2023 marked a significant breakthrough for generative AI. It evolved from a novel technology to a mainstream tool, deeply integrated into businesses and creative processes. ChatGPT, a prominent example, showcased the potential of GenAI in automating complex tasks such as content creation, software development, and image generation. This mainstream adoption is changing the game, compelling organizations to adopt private large language models (LLMs) not just as an enhancement but as a necessity to stay competitive​​.

The practical applications of GenAI are vast. In content creation, for instance, it’s no longer about automating mundane tasks; it’s about crafting unique, engaging content that resonates with audiences on a deeper level. Similarly, in software development, GenAI is not just streamlining processes but also enabling the creation of more sophisticated, user-centric software. Tech companies have started training their workforce to be able to use AI tools and increase productivity. 

The underlying implication is profound: organizations leveraging GenAI are not just optimizing their operations; they’re redefining their industry landscapes.

Challenges and Innovations in AI Hardware

However, this rapid growth in AI capabilities is not without its challenges, particularly in hardware. A major concern as we step into 2024 is the global shortage of GPU processors, critical for running AI applications. This shortage is a result of increased demand from big companies seeking to internalize AI capabilities. Notably, NVIDIA, a major GPU manufacturer, is struggling to meet this skyrocketing demand​​.

This challenge is spurring innovation in AI hardware. Experts at Stanford, including professors like Kunle Olukotun and Chris Re, are exploring low-power alternatives to current GPUs. These efforts are crucial in democratizing AI technology, making it accessible beyond the big players. The development of new hardware solutions is not just about meeting current demands; it’s about future-proofing AI technology, ensuring that it remains sustainable and accessible as it becomes increasingly woven into the fabric of our society​​.

AI-Powered Agents and Multimedia

The landscape of AI is set to evolve remarkably in 2024, with a significant shift towards more interactive and multi-functional AI agents. The previous year laid the groundwork, mainly focusing on chat-based AI interactions. But the upcoming year promises to leap beyond this, enabling AI agents to perform real-world tasks like making reservations, planning trips, and seamlessly connecting to various services. This evolution marks a transition from AI as a conversational tool to a practical assistant capable of executing tasks autonomously​​.

In multimedia, AI’s potential is expanding rapidly. Until now, the focus has primarily been on language and image models. However, the integration of video processing is on the horizon. This advancement is particularly intriguing because video data provides a new dimension of unfiltered, continuous information that AI models haven’t processed before. It could lead to a more profound understanding of real-world events and behaviors, significantly enhancing AI’s predictive and analytical capabilities​​.

Importance of AI Governance and Ethics

As AI becomes increasingly integrated into various aspects of society, the need for robust governance and ethical frameworks grows more urgent. In 2024, we can expect more concrete actions and policies in this area. Governments and organizations worldwide are recognizing the risks associated with bias, inequality, and discrimination in AI algorithms. Consequently, there’s a move towards implementing guardrails and governance policies to mitigate these risks. The U.S. White House Executive Order and emerging regulations in Europe are indicative of this global shift towards responsible AI usage​​.

In addition, the calls for transparency and responsible development in AI are expected to grow stronger. This focus on ethical AI development reflects a broader societal demand for technology that not only advances capabilities but also respects and protects human rights and values. This shift is not just about avoiding harm; it’s about leveraging AI in a way that positively contributes to society, fostering trust and acceptance among the general public​​.

AI in the Workplace

The impact of AI on the workforce is a crucial trend for 2024. AI adoption in the workplace is enhancing processes, boosting productivity, and reshaping income structures. It’s a double-edged sword, however, as it also brings the potential for significant job displacement. To counterbalance this, there will be a heightened emphasis on the reskilling and upskilling of employees. The future workplace will likely see the emergence of new roles such as AI ethicists and prompt engineers, illustrating the transformative effect of AI on job landscapes​​.

A Goldman Sachs report suggests that AI could trigger a productivity boom, potentially increasing the total annual value of global goods and services by 7%. This signifies a profound shift in the nature of work, where certain skills will become obsolete while others, like analytical judgment and emotional intelligence, will become more valuable. The integration of AI in the workplace is not just about automation; it’s about creating a more dynamic, skill-focused, and efficient workforce​​.

AI in Various Industries

In 2024, we’ll witness AI’s growing influence across a wide array of industries, reshaping them in innovative ways. The healthcare sector, for example, will see AI-driven enhancements in patient communication, disease detection, and support for healthcare professionals. In education, AI is expected to revolutionize learning experiences through innovative content and personalized tutoring systems. Manufacturing will benefit from AI in rapid prototyping, digital twinning, and optimizing production processes​​.

Each industry will experience AI’s transformative power differently, but the common thread is the move toward efficiency, precision, and personalization. For instance, in e-commerce, AI is set to offer more tailored shopping experiences, while in agriculture, it could lead to more efficient and sustainable farming practices. There are many case studies on such solutions built by tech companies like Mantra Labs. This widespread application signifies AI’s versatility and its potential to solve industry-specific challenges​​.

Data Protection and Privacy in the Age of AI

As AI technologies become more pervasive, the importance of data protection and privacy is increasingly highlighted. AI TRiSM (Trust, Risk, and Security Management) is gaining prominence as a framework to help organizations comply with data privacy regulations. By 2026, it’s expected that companies using AI TRiSM to manage their AI systems will significantly improve decision-making by eliminating inaccurate or fake data​​.

This trend underscores the necessity of balancing AI’s potential with the need to protect individual privacy. As AI systems often contain sensitive personal data, ensuring their security and compliance with data privacy laws is crucial for maintaining public trust and ethical standards in AI deployment.

Personalization Through AI

Personalization is a key trend in AI for 2024, especially in app development. Gartner predicts that by 2026, a third of all new apps will use AI to create personalized and adaptive user interfaces, a significant increase from today’s numbers. This shift is driven by AI’s ability to analyze user data and preferences, offering tailored content and experiences. Companies excelling in AI-powered personalization are expected to generate significantly more revenue from these activities compared to their peers​​.

Emergence of Quantum AI

Quantum AI, the fusion of quantum computing and AI, is an emerging field poised to open new possibilities in various domains. It could revolutionize financial modeling, and drug discovery, and even contribute to the development of Artificial General Intelligence (AGI). The global Quantum AI market is anticipated to reach a significant value by 2030, growing at a robust rate. This synergy between quantum computing and AI has the potential to dramatically enhance computational power and efficiency, paving the way for groundbreaking advancements​​.

Legislative Landscape for AI

The advancement and integration of AI into daily life necessitate the development of comprehensive legislation to govern its use. Laws and regulations will be crucial in ensuring AI is used responsibly and ethically. As AI can be utilized for both positive and negative purposes, having a legal framework in place is essential for guiding its development and application in a manner that aligns with societal values and norms​​.

Wrapping Up

Looking ahead to 2024 and beyond, AI is set to continue its transformative journey, impacting every facet of our lives. From enhancing workplace productivity to reshaping entire industries and necessitating robust governance frameworks, AI’s potential is boundless. As we embrace these advancements, it’s crucial to balance innovation with ethical considerations, ensuring AI’s development benefits society as a whole. The future of AI is not just about technological prowess; it’s about how we harness this power to create a more efficient, equitable, and sustainable world.

Cancel

Knowledge thats worth delivered in your inbox

10 Analytics Tools to Guide Data-Driven Design

Analytics are essential for informing website redesigns since they offer insightful data on user behavior, website performance, and areas that may be improved. Here is a list of frequently used analytics tools to guide data-driven design that can be applied at different stages of the website redesign process. 

Analytics Tools to Guide Data-Driven Design

1. Google Analytics:

Use case scenario: Website Audit, Research, Analysis, and Technical Assessment
Usage: Find popular sites, entry/exit points, and metrics related to user engagement by analyzing traffic sources, user demographics, and behavior flow. Recognize regions of friction or pain points by understanding user journeys. Evaluate the performance of your website, taking note of conversion rates, bounce rates, and page load times.

2. Hotjar:

Use case scenario: Research, Analysis, Heat Maps, User Experience Evaluation
Usage: Use session recordings, user surveys, and heatmaps to learn more about how people interact with the website. Determine the high and low engagement regions and any usability problems, including unclear navigation or form abandonment. Utilizing behavior analysis and feedback, ascertain the intentions and preferences of users.

3. Crazy Egg:
Use case scenario: Website Audit, Research, Analysis
Usage: Like Hotjar, with Crazy Egg, you can create heatmaps, scrollmaps, and clickmaps to show how users interact with the various website elements. Determine trends, patterns, and areas of interest in user behaviour. To evaluate various design aspects and gauge their effect on user engagement and conversions, utilize A/B testing functionalities.

4. SEMrush:

Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct keyword research to identify relevant search terms and phrases related to the website’s content and industry. Analyze competitor websites to understand their SEO strategies and identify opportunities for improvement. Monitor website rankings, backlinks, and organic traffic to track the effectiveness of SEO efforts.

5. Similarweb:
Use case
scenario: Research, Website Traffic, and Demography, Competitor Analysis
Usage: By offering insights into the traffic sources, audience demographics, and engagement metrics of competitors, Similarweb facilitates website redesigns. It influences marketing tactics, SEO optimization, content development, and decision-making processes by pointing out areas for growth and providing guidance. During the research and analysis stage, use Similarweb data to benchmark against competitors and guide design decisions.

6. Moz:
Use case scenario: Research, Analysis, SEO Optimization
Usage: Conduct website audits in order to find technical SEO problems like missing meta tags, duplicate content, and broken links. Keep an eye on a website’s indexability and crawlability to make sure search engines can access and comprehend its material. To find and reject backlinks that are spammy or of poor quality, use link analysis tools.

7. Ahrefs:
Use case scenario:
Research, Analysis, SEO Optimization

Usage: Examine the backlink profiles of your rivals to find any gaps in your own backlink portfolio and possible prospects for link-building. Examine the performance of your content to find the most popular pages and subjects that appeal to your target market. Track social media activity and brand mentions to gain insight into your online reputation and presence.

8. Google Search Console:

Use case scenario: Technical Assessment, SEO Optimization
Usage: Monitor website indexing status, crawl errors, and security issues reported by Google. Submit XML sitemaps and individual URLs for indexing. Identify and fix mobile usability issues, structured data errors, and manual actions that may affect search engine visibility.

9. Adobe Analytics:
Use case scenario:
Website Audit, Research, Analysis,
Usage: Track user interactions across multiple channels and touchpoints, including websites, mobile apps, and offline interactions. Segment users based on demographics, behavior, and lifecycle stage to personalize marketing efforts and improve user experience. Utilize advanced analytics features such as path analysis, cohort analysis, and predictive analytics to uncover actionable insights.

10. Google Trends:

Use case scenario: Content Strategy, Keyword Research, User Intent Analysis
Usage: For competitor analysis, user intent analysis, and keyword research, Google Trends is used in website redesigns. It helps in content strategy, seasonal planning, SEO optimization, and strategic decision-making. It directs the production of user-centric content, increasing traffic and engagement, by spotting trends and insights.

About the Author:

Vijendra is currently working as a Sr. UX Designer at Mantra Labs. He is passionate about UXR and Product Design.

Cancel

Knowledge thats worth delivered in your inbox

Loading More Posts ...
Go Top
ml floating chatbot