By Maciej Dziergwa, Founder & CEO of STX Next
In 2022, many organizations had expected a continuation of the post-pandemic boom. Instead, they were met with a rude awakening—widespread inflation rises, energy shortages, and the downturn of the tech industry.
As a global recession appears imminent, business leaders are rightly worried about how best to position their companies to not only survive but succeed in 2023. The first step to achieving this is understanding the tech trends that will dominate the coming year, so that you can leverage them for your benefit early.
1. Increased emphasis on transparent data governance
Data privacy trust is at an all-time low—that’s an alarming fact. Cisco’s State of Consumer Data Privacy Report revealed that “only 21% of users trust established global brands to keep their personal information secure.”
In 2023, big companies will likely move to earn users’ trust by adopting user-first data governance. This means users will be actively involved in determining if and how their data is collected, how it is processed, how it is stored, and how it is disposed of. In addition, more users are bound to opt out of access requirements like sharing their data with third-party applications.
Businesses that adopt radical transparency will win in this new era of user-first data governance.
2. Adaptive AI everywhere
In 2023, more businesses will lean on adaptive AI systems to scale efficiency, speed up their time-to-market, and maximize scarce resources.
Adaptive AI systems are flexible and equipped for real-time iterations. They quickly adjust to changing real-world circumstances while in production by interpreting behavioral patterns in datasets. A good example are Generative AI models, which automatically train on the data fed into them to improve output.
There are several ways to incorporate adaptive AI systems into your standard workflow, including:
- training adaptive AI systems with existing data before deploying these systems independently;
- creating predictive data models, so your organization is better equipped to handle rapid future changes;
- continuously iterating employee training materials based on real-time data feedback.
3. The rise of the metaverse
By 2023, the metaverse will become more mainstream through increased adoption in marketing, events, and business operations. Here are our predictions:
More businesses will adopt virtual shopping to reach more customers and deliver immersive user experiences. Virtual events will move to the metaverse, so attendees enjoy the same experience regardless of where they are. Remote organizations will use the metaverse to create stronger company cultures. The metaverse will make employee onboarding sessions, all-hands meetings, and watercooler chats more engaging.
As the metaverse moves into the mainstream, the focus will be on creating affordable technology that enables mass adoption. Big tech companies like Apple, Google, and Microsoft will lead the way in creating advanced avatar systems, full-body haptic suits, and headsets that make it easier for the metaverse to simulate reality.
In addition, stakeholders will ensure that standards are in place to facilitate the seamless integration of multiple metaverse platforms.
Here’s how you can tap into this trend:
- Identify opportunities to optimize digital businesses or create new products based on metaverse technologies.
- Develop innovative metaverse products and solutions.
- Implement proactive data governance guidelines to protect your business and customers’ data in the virtual world.
4. Ethical regulations for AI usage
In 2022, mainstream industries like software engineering, content marketing, and digital art rapidly adopted AI to improve efficiency and scale output—often without paying much attention to ethical usage.
As a matter of fact, data from FICO’s State of Responsible AI report shows that about 78% of organizations are “poorly equipped to ensure the ethical implications of using new AI systems.”
In the coming year, stakeholders will implement protective policies to close ethical loopholes in AI deployment and better streamline how companies use this technology. Most of these regulations will focus on:
- improving data bias detection,
- streamlining copyright for generative AI models,
- standardizing AI model deployment and management.
The work on this has already begun. For instance, the European Union is already working on the AI Liability Directive, which will hold companies accountable for any harm caused by the AI technology they deploy. It will also require them to provide information on training models and how they use artificial intelligence in day-to-day work.
Speaking to AI News on the need for regulations like the EU AI Act, Cal Al-Dhubaib, CEO of Pandata, had this to say:
“In some cases, regulation is long overdue. Regulation has hardly kept up with the pace of innovation. Just like GDPR created a wave of change in data privacy practices and the infrastructure to support them, the EU AI Act will require organizations to be more disciplined in their approach to model deployment and management. Organizations that start to mature their practices today will be well prepared to ride that wave and thrive in its wake.”
AI is not going anywhere; rather, it will become a core tool for maximizing business performance. That’s why IT leaders must start adapting their practices now to meet ethical standards. Some steps you can take include:
eliminating AI algorithm bias to limit discrimination and skewed results,
prioritizing data privacy and protection to improve trust,
implementing transparency so that your customers know when AI is being used and are able to opt out of it.
5. Accelerated cloud adoption
Industry cloud platforms have already gained some degree of popularity over the past year. About 40% of North American and European enterprises have already begun adopting industry cloud platforms.
However, in 2023, we expect enterprise businesses to lean more heavily on these cloud platforms to manage, connect, and automate their business processes.
There are several reasons for this change, but the most important one is scalability. In Gregor Petri’s words, “Industry cloud platforms turn a cloud platform into a business platform, enabling an existing technological innovation tool to also serve as a business innovation tool.” A great example of this is IBM Cloud for Financial Services.
Unlike out-of-the-box solutions that can only perform a single function, industry cloud platforms are aggregations of software solutions that can execute a wide range of industry-specific tasks.
This means that instead of investing in numerous software, enterprise businesses rely on a single platform that supports a complete set of industry-relevant functionalities, which enables these organizations to scale efficiently. It’s like having your own software ecosystem.
Before integrating industry cloud platforms into your existing business workflow, there are three things you need to do first:
- Determine where exactly the cloud platform fits in your business workflow. Consider investing in cloud platforms that complement your existing tool stack rather than replacing what you have entirely.
- Set up business technology and cross-functional teams to own the decision-making process and manage the overall technology deployment.
- Enforce strict rules around using industry cloud platforms. Determine when it should be used as an add-on to your existing workflow and when to use it to create and implement new systems.
6. The rise of the AI of Things (AIoT)
The AI of Things is an area of artificial intelligence involving the intersection of AI and the Internet of Things. It refers to using AI technologies in IoT devices and systems to achieve improved functionality and performance.
For example, organizations can use first-party data collected by Internet of Things devices—like Siri and Alexa—to train AI models to be more accurate and objective.
The AI of Things is expected to enable IoT devices to autonomously collect and analyze data, make decisions, and take actions without human intervention. This will allow the development of more innovative and efficient IoT systems and applications in the coming year.
7. Mainstream adoption of Web3 technologies
Data privacy concerns regarding traditional Internet platforms will drive the mass adoption of Web3 technologies in the coming year.
“People are starting to wake up to the fact that in the digital world, all of our interactions are permanent, [and] we have no idea who is watching anything,” Alex Pruden, Chief Executive Officer of Aleo, said in an interview with The Drum.
“It is a totally new universe that humanity is trying to wrap their heads around. […] This is why you’ve seen crypto be adopted more and more: people who are more tech-forward as they realize the implications, and I think slowly but surely, people will come around to see that we have to have protections, we need to use cryptography to protect our information online,” Pruden adds.
Web3 technologies for everyday use like communication, business activities, or financial transactions will actively compete with their traditional counterparts. More people will replace formal agreements with smart contracts, fiat transactions with cryptocurrencies, and traditional social media platforms such as Twitter with Web3 alternatives like Mastodon.
How can traditional institutions prepare to survive and thrive in a Web3-driven world? The key is customer-centricity, says Suad Seferi.
“To have their businesses in the Web3 realm, companies must be ready to operate in an abnormal environment where users will finally be put at the center of all business processes. Ecosystem companies focusing on security and education will surely become the fastest-growing brands in the new Web3 realm.”
For IT companies worldwide, this means:
- holding your business to the highest transparency standards,
- growing communities on Web3 platforms,
- investing in data privacy and security.
When times are tough, innovation-driven businesses that adapt quickly to technological changes stand out from the competition.
2023 will be no different. The organizations that will win are those willing to experiment with new technologies and invest in creating infrastructures to support these experiments without exposing customers to risk.
At STX Next, we’re no strangers to emerging technologies and the challenges that come with implementing them in software projects, whether it’s machine learning or data engineering. Our years of experience in fintech development have also taught us a thing or two about security, risk, and scalability.