2024 Key Technology Trends

“The best way to predict the future is to create it.” This quote is credited to both Abraham Lincoln and Peter Drucker. 

The continually evolving need for a focus on Cybersecurity and Data has been highlighted due to GenAI’s unparalleled growth and potential for misuse. In addition, technologies like Extended Reality are now hitting a level of maturity, allowing businesses to improve the customer experience.

As CIOs and their teams begin to adapt their technology portfolios to these new realities, we assessed our work with clients and researched leading voices in the industry to explore the most important trends we believe will impact organizations.  Our aim is to help senior executives shape their 2024 priorities and determine how they will use technology to sustain growth and create a technology-driven competitive advantage.

Though the concept of Artificial Intelligence is not new, new solutions and rapidly increasing computing power have opened many new possibilities for the application of AI in the business setting.

AI / Generative AI

Generative AI is increasingly recognized as a powerful technology catalyst, playing a transformative role across various industries by reshaping processes. Gen AI unlocks new possibilities by taking assistive technology to the next level, reducing application development time, and offering enormous potential to increase productivity by automating activities.

• Gen AI enables data extraction with text-based questioning, chat functionalities and code generation.
• Image generation transforms text into images, enhancing artistic content creation, particularly in the field of marketing.
• Image description utilizes raw data (images) to generate descriptive sentences. This technology is beneficial for mobile and desktop applications, providing instant access.
• Data visualization transforms raw data into dashboard templates, simplifying reporting for top management.

Gen AI can help to build a more empowered workforce, assisting employees to work more effectively and efficiently.

• Gen AI enhances the employee experience by suggesting code updates, drafting marketing campaigns, and expediting the training process.
• Middle managers, positioned closest to employees, benefit by overseeing new work streams and focusing on high-value leadership tasks.
• Organizations can revamp talent management practices using gen AI for personalized outreach, improved onboarding, and administrative streamlining.

We recommend organizations invest in understanding the technology, provide ongoing education, and navigate the rapidly accelerating landscape of Gen AI which brings huge potential for business improvement.

AI Augmented Development

AI Augmented development has the power to transform software creation by shifting the focus from coding to aligning efforts with strategic goals and measurable outcomes.

With AI's support, the entire software development lifecycle can be streamlined, covering feature definition, code generation, and testing. While this doesn't eliminate the need for software engineers, it envisions a future where the product team creates a functional product for A/B testing, subsequently refined by the engineering team for scalability.

It is crucial to recognize that AI-augmented development goes beyond code writing—it's about aiding developers in constructing impactful software that contributes to organizational success.

Intelligent Applications (integrated with AI)

Intelligent applications have the potential to revolutionize the structure of work by introducing optimization, advisory services, and decision-support functionalities into the process-centric workflows of enterprise business applications.

These applications utilize a spectrum of advanced AI techniques, including machine learning, natural language processing, and computer vision, to:

• Analyze data
• Make accurate predictions
• Automate a variety of tasks

Large Language Models (LLMs)

A LLM is a sophisticated AI system that has learned from a vast amount of text data. Training enables the AI to understand and then generate responses in conversations and requires:

1. Data Collection: LLMs require an extensive textual database from diverse sources to ensure adaptability and generalization across various contexts.
2. Model Architecture: LLMs utilize transformers and attention mechanisms to predict the next word in a sentence. The model's architecture involves configuring parameters (weights) that signify correlations in meaning or usage.
3. Infrastructure: Adequate computational architecture is essential for both the training and usage phases of LLMs. The computational capacity required is directly proportional to the size of the training data and the number of weights to be calculated.

Responsible AI

Regulatory and ethical considerations must be proactively addressed and accompany the​ development of Gen AI solutions in business.​ During the design phase, key aspects to address include:

• Personal Data and Consent: clarify the purpose for obtaining consent for data consumed by AI.
• Intellectual Property: assess the potential use of data subject to intellectual property rights.
• Hallucinations and Veracity: evaluate the risks associated with the AI generating inaccurate information.
• Ethics and Moderation: Understand the potential risks associated with the AI's responses or the production of unethical content.

AI Focused Regulations

Countries are seeing the need to develop regulations to help manage the impact of AI on society.  For example, the European Union (EU) AI Act aims to regulate AI as part of its digital strategy for improved development and utilization. AI offers various benefits, including enhanced healthcare, safer transport, efficient manufacturing, and sustainable energy. In April 2021, the European Commission introduced the first AI regulatory framework, categorizing AI systems based on their risk levels, with corresponding levels of regulation.

Cybersecurity, Data Privacy, and Regulatory Compliance continue to be regular topics for discussion at the Board level.  Organizations are concerned about the risks they face, both from external threats and from the reputational risk of failing to protect organizational or customer information.

Cyber Resilience

Cybersecurity remains a key concern for organizations in 2024. Security resilience is confronting a new world where everyone and everything is connected. Businesses are operating as integrated ecosystems with boundaries between the corporations, customers, suppliers and partners all blurring. Key trends to watch for:

1. AI-driven Threat Detection: AI algorithms will be integrated with threat detection capability helping to analyse vast amounts of data to indicate threat patterns.
2. Continuous Threat Exposure Management (CTEM): A systematic approach to assess and manage the accessibility, exposure, and exploitation risk of physical or digital assets.
3. Incident response planning: Planning, documenting, and practicing how the organization will respond to data breaches, data leaks, cyber-attacks, and security incidents.
4. System Hardening: Keeping your organization safe from intruders by reducing the attack surface as much as possible.

Data Privacy & Regulatory Compliance

Because of an increase in cyber-attacks and continuously evolving global regulations such as the Digital Operational Resilience Act (DORA), organizations are increasingly concerned with data privacy and regulatory compliance. CIOs need to ensure compliance with data protection regulations and avoid potential legal and/or reputational damage.

Gen AI is driving a greater need for data, making data an even more critical asset.

1. Evaluate Data Availability: Assess the quality and quantity of available data within your organization. The training of generative AI models demands extensive and diverse datasets.
2. Data Cleansing: Eliminate noise, inconsistencies, and irrelevant information from the dataset.
3. Data Augmentation: In cases of limited datasets, artificially expand them by applying diverse transformations or incorporating synthetic data points. GenAI can also be utilized for data creation or dataset preparation.
4. Data Encoding: Transform the data into a suitable format for training, often involving tokenization for text data or image preprocessing for image data.
5. Data Quality and Quantity: Securing, cleaning, and preparing high-quality data for model training can pose a significant challenge. Many organizations may encounter limitations in this regard.

A few years ago, these technologies would have been considered as leading-edge solutions.  Now, they have become more established and are being used in a variety of new ways to help businesses achieve reduced costs, improved revenues and customer experience.

Sustainable Technology/Green IT

Helping to address environmental concerns, a paradigm shift is taking place in favour of sustainable technologies. This shift involves a new approach to the IT lifecycles of services from design to disposal.  As such, sustainable technology must become a key factor in corporate strategy and management responsibility.

1. Energy-efficient, environmentally friendly frameworks: the heart of sustainable IT lies in improving the energy efficiency of IT services. By integrating solutions such as advanced analytics, emissions management software and AI, companies not only optimize their energy consumption, they also contribute to global sustainability efforts.
2. Responsible IT practices: sustainable technology involves the conscientious design and use of IT systems and software, aiming to minimize environmental impact while maintaining performance, aiming to balance ecological responsibility and technological progress.
3. Digital solutions for ecological balance and human rights: with technologies such as AI, crypto-currencies and cloud computing being widespread, there are growing concerns about their impact on the environment. Sustainable technology acts as an environmental steward, ensuring these digital solutions support long-term ecological balance and human rights.
4. Economic and social viability of the technology life cycle: sustainable technology also ensures that the technology and processes we use are economically viable and socially acceptable throughout their life cycle. This aspect of sustainability considers the total cost of ownership, including the disposal or recycling of technology products at the end of their life.

Extended Reality

Extended Reality solutions can reduce costs, increase revenue and productivity, and improve employee and customer experience. CIOs should consider adopting Extended Reality to unlock new business value and create new content and services. As the world continues to become more virtual, Extended Reality will play an even larger role in our personal and professional interactions. Examples include augmented reality training and the creation of unique customer interfaces.

Blockchain

By 2024, it is estimated that Blockchain will reduce bank infrastructure costs by $15-20 billion annually. CIOs should investigate how Blockchain can provide end-to-end visibility, reducing fraud and errors. Additionally, decentralized finance (DeFi) applications are gaining traction with an estimated $200 billion in value to be unlocked. Firms are turning to Blockchain to replace slow, centralized, and less secure systems.

Web3

Web3 is a fundamental development in digital technology that blends Extended Reality and Blockchain capabilities to improve the user experience, safeguard personal data, and allow users to own and govern their assets. By increasing interactions and delivering customized experiences, Web3 will unlock opportunities for improved communication, entertainment, and business development.

“When digital transformation is done right, it’s like a caterpillar turning into a butterfly, but when done wrong, all you have is a really fast caterpillar”

George Westerman, MIT Sloan Initiative on the Digital Economy

Sia Partners works with organizations across the globe.  In an increasingly connected world where businesses are global and operating 24/7 in multiple eco-systems, we believe the IT organization is uniquely placed to offer a strategy to leverage opportunities offered by new technologies to create competitive advantage, enable higher productivity, enhance the customer experience, and positively impact the bottom line.

Organizations cannot risk standing still. We recommend CIOs carefully review these key trends and work with their stakeholders to determine how these trends can unlock additional value for your organization.

1. How are cybersecurity and data highlighted in the context of GenAI's growth?

   GenAI's growth underscores the increasing need for cybersecurity measures and responsible data usage due to its potential for misuse and the generation of synthetic data.

2. What role does Extended Reality play in improving customer experience for businesses?

   Extended Reality enhances customer experience by offering immersive and interactive experiences, such as augmented reality training and unique customer interfaces.

3. What is Generative AI, and how does it impact various industries?

   Generative AI creates synthetic data and content, transforming processes across industries by enhancing productivity, automating activities, and enabling new possibilities.

4. What are some specific applications of Generative AI, such as image generation and data visualization?

   Generative AI applications include text-based questioning, chat functionalities, image generation, image description, and data visualization.

5. How does Gen AI empower the workforce, and what benefits does it offer to organizations?

   Gen AI empowers employees by suggesting code updates, drafting marketing campaigns, expediting training, and enabling middle managers to focus on high-value leadership tasks.

6. What is AI Augmented Development, and how does it transform software creation processes?

   AI Augmented Development shifts the focus from coding to aligning efforts with strategic goals and measurable outcomes, streamlining the software development lifecycle and aiding in constructing impactful software.

7. How do Intelligent Applications utilize advanced AI techniques to revolutionize workflows?

   Intelligent Applications utilize machine learning, natural language processing, and computer vision to analyze data, make predictions, and automate tasks, revolutionizing enterprise workflows.

8. What are Large Language Models (LLMs), and what are their key components?

   LLMs are advanced AI systems trained on vast textual datasets, utilizing transformers and attention mechanisms to predict the next word in a sentence.

9. What are the key aspects of responsible AI development that organizations need to address?

   Key aspects include clarifying consent for personal data, assessing intellectual property rights, evaluating risks associated with inaccurate information generation, and understanding potential ethical concerns.

10. How are AI-focused regulations evolving globally, and what impact do they have on businesses?

    AI-focused regulations aim to manage the impact of AI on society, with initiatives like the EU AI Act categorizing AI systems based on risk levels and corresponding levels of regulation.

11. What are the key trends in cybersecurity for 2024, such as AI-driven threat detection and incident response planning?

    Key trends include AI-driven threat detection, continuous threat exposure management (CTEM), incident response planning, and system hardening to mitigate cyber risks.

12. Why are data privacy and regulatory compliance increasingly important for organizations, and how does Gen AI contribute to these concerns?

    Organizations face increasing cyber threats and regulatory pressures, making data privacy and compliance crucial. Gen AI contributes by requiring high-quality data for training, leading to enhanced data privacy practices.

13. What are some best practices for evaluating data availability and quality for Gen AI training?

    Best practices include assessing the quality and quantity of available data, cleansing data to eliminate noise, augmenting data when necessary, and encoding data in suitable formats for training.

14. How have sustainable technologies evolved and become integrated into corporate strategies?

    Sustainable technologies have become integrated into corporate strategies through improved energy efficiency, responsible IT practices, and considerations for economic and social viability throughout the technology lifecycle.

15. What role do Extended Reality solutions play in reducing costs and improving productivity?

    Extended Reality solutions reduce costs and improve productivity by offering immersive training experiences, enhancing customer interactions, and enabling new content and services.

16. What potential benefits does Blockchain offer for reducing infrastructure costs and enhancing visibility in banking?

    Blockchain reduces infrastructure costs by providing end-to-end visibility, reducing fraud and errors, and enabling decentralized finance applications to unlock significant value.

17. How does Web3 combine Extended Reality and Blockchain capabilities to improve user experiences and asset ownership?

    Web3 combines Extended Reality and Blockchain to improve user experiences, safeguard personal data, and enable users to own and govern their assets, unlocking opportunities for improved communication, entertainment, and business development.

18. What are some estimated impacts or predictions for the adoption of Blockchain and Web3 technologies by 2024?

    By 2024, Blockchain is estimated to significantly reduce bank infrastructure costs and unlock value in decentralized finance applications. Web3 technologies are expected to revolutionize digital interactions and create new opportunities for businesses and users alike.