The year 2022 was marked by geopolitical instability, fast advancements in new technologies, and financial downturns, all of which had a significant impact on the world’s economy and global trends. As we move forward into 2023, it’s important to take note of the digital trends that will shape the technological landscape in the coming year.
The advancements in digital technologies like ChatGPT, and the growing demand for artificial intelligence and automation, are expected to dominate the tech industry. However, the fast pace of technological advancement in 2023 is not without its challenges. The rise of geopolitical instability and the effects of the pandemic led to massive tech layoffs, while the financial downturn may impact the adoption and implementation of new technologies. In this article, we’ll examine my digital trend predictions for 2023 and what they could mean for businesses, individuals, and the technology industry as a whole. This article will provide a high level overview of the trends with follow up articles including a deeper dive into each of the trends.
1. Democratisation of digital tools, including AI and low-code.
This trend is driven by the need to empower people of all skill levels to take advantage of digital technologies and leverage their benefits to improve their lives and businesses.
One of the key aspects of the democratization of digital tools is the increasing availability of AI tools, like ChatGPT and DALL-E. These tools are becoming more accessible to non-technical users, enabling them to create sophisticated chatbots, conversational interfaces and tapping into universal knowledgebase, without requiring deep technical knowledge. This democratization of digital tools will drive innovation and enable new use cases across a wide range of industries: customer service, technology, education, creative industries, healthcare, marketing, etc.
AI technologies, like ChatGPT, Github co-pilot, will also help engineers to be even more productive. With the increasing complexity of software development, engineers are under pressure to deliver high-quality code in less time. AI tools can help by helping engineers to write more predictable tasks such as testing, documentation, simple funcitons and classes, freeing up engineers to focus on more creative and high-value tasks. Over the last year, I’ve been testing Github co-pilot and recently ChatGPT, and while these techologies speed up my development efforts, there is still a lot of manual inputs and edits required from the engineer.
Another area where AI is expected to have a significant impact is in the creative industries. AI technologies, like DALL-E and ChatGPT, will become a de-facto tool for creatives, allowing them to generate new ideas, designs, and content. This will help to automate repetitive tasks and free up creative professionals to focus on more complex and high-value work. One example that I recently played with is JIS.AI, application of AI for marketing that automates marketing communication, creates campaigns and marketing materials.
Search technologies that were previously available only to big tech companies will become more affordable for non-tech native large corporates. This will enable these organizations to leverage the power of advanced search technologies to improve productivity, gain insights, and enhance decision-making.
Another aspect of tech democratisation trend is the increasing use of low-code platforms. These are visual development environments that enable non-technical users to create software applications without having to write code. Low-code platforms will make it easier for businesses to build custom applications tailored to their specific needs, enabling them to be more agile and responsive to changing market conditions.
2. Productionisation of machine learning systems and adaptive machine learning.
The ability to change behavior after deployment and retrain as needed will enable machine learning systems to adapt to change in environment (such as consumer, political) and help businesses to make better decisions.
Adaptive machine learning algorithms will be better suited to detect changes in the data (such as data drift) and adjust the model accordingly. They can do this by constantly monitoring the performance of the model and data distribution and making updates based on new data.
There will be a further push for productionization of data and AI within companies. This will involve creating seamless MLOps processes for managing data and deploying machine learning systems in production. This will help to ensure that machine learning systems are tested, with right level of governance and integrated into the core business processes of a company.
3. Strengthening the AI foundations: technology and talent
As AI is becoming a competitive advantage to more and more companies, it is increasingly importat to strenthen the foundations: data architectures, such as data mesh; renewing the tech stack, to save future costs and enabling new use cases; process standartisation across the business.
Further adoption of cloud computing will also play an important role in supporting AI initiatives in 2023, as cluster computing and high-performance computing will be increasingly important for scaling applications, reducing costs and, in certain industries, training large-scale models like chatgpt.
In addition to investments in technical foundations, there will also be a renewed focus on ethical aspects of AI, explainability, and governance. As AI becomes more integrated into business operations, companies will need to ensure that their AI systems are transparent, accountable, and aligned with ethical and legal standards. This will involve developing new tools and frameworks for explaining and auditing AI systems, as well as establishing clear governance and oversight mechanisms for AI initiatives.
There will be the continued high demand for AI talent, despite the recent massive layoffs in some of the top tech companies. Talking to some of the top company executives, while there is a temporary hiring freeze, there will be need for AI talent later this year.
4. Cybersecurity.
In the year 2023, cybersecurity will remain one of the most important digital trends, especially in the wake of recent high-profile attacks on companies such as Optus and Medibank, which have led to millions of personal data records, including driver license numbers and passport details, being stolen.
One of the key themes in cybersecurity for the coming year will be the automation of security processes through DevSecOps. This involves running code through a series of automated security tests before it is deployed, which can help identify vulnerabilities, outdated libraries, and other security issues. This approach not only increases the speed of development but also reduces the risk of security breaches by catching bugs early on.
Another aspect of cybersecurity in 2023 will be the standardization of security best practices. With so many different technologies and approaches to security, it can be difficult for organizations to determine what works best for them. As a result, industry standards and guidelines are likely to emerge, providing a common set of practices that can be adopted by all organizations.
Trust architectures and digital identity will also be important trends in cybersecurity in 2023. The evolution of zero-trust architectures, digital identity solutions, and the development of protocols and controls for digital solutions will provide greater security for interconnected systems. This will enable on-demand access to products and services without compromising security.
Lastly, there will be a further leverage of AI technologies to catch anomalies in systems. As cyber threats become more sophisticated, it is becoming increasingly difficult for humans to keep up. AI and machine learning technologies can help by detecting unusual behavior and identifying potential threats before they become a problem.
In conclusion, cybersecurity will continue to be a critical digital trend in 2023. With the increasing frequency and severity of cyber attacks, organizations must take proactive steps to ensure the security of their data and systems. The trends towards automation, standardization, trust architectures, and AI-based security solutions will help organizations to stay ahead of the curve and keep their data safe.
5. Sustainability.
Although this is still an early stage in tackling sustainability with digital technologies, the coming year will likely see significant advancements in this field. With climate change becoming an increasingly urgent issue, companies are recognizing the importance of sustainability not only for ethical reasons but also as a competitive advantage.
In the technology industry, sustainability is being approached in a variety of ways. For example, there is an increasing focus on renewable energy sources to power data centers and cloud computing facilities. Companies are also exploring the use of artificial intelligence and machine learning to optimize energy usage, reduce waste, and increase efficiency in their operations.
Another area where digital technologies are making a significant impact on sustainability is through the Internet of Things (IoT). Smart devices and sensors are being used to collect data on energy usage, water consumption, and other environmental factors. This data can then be used to identify inefficiencies, optimize resource usage, and reduce waste.
In the coming year, we can expect to see more large companies tuning to sustainability as a competitive advantage. With consumers increasingly demanding eco-friendly products and services, sustainability is becoming an important factor in purchase decisions. As a result, companies that prioritize sustainability are likely to have a significant advantage over their competitors.
This article reflects my personal views and opinions only, which may be different from the companies and employers that I am associated with.