Going into 2022, we had high hopes and a cautious optimism that things would change for the better after two years of pandemic. Now, it's time for an assessment of the year to see whether our hopes materialized or unexpected developments rendered our predictions irrelevant.
2022 was a good year for low-code/no-code (LCNC) platforms, just as we predicted. The enterprise segment was particularly enthusiastic in adopting these tools and using them to create internal tools and automate tasks. It looks like the B2C segment will take some time to mature before it offers a viable business to low-code/no-code (LCNC) companies. There are mainly two reasons for that: Despite requiring little to no coding skills, people still benefit immensely from algorithmic thinking if they are to tap into the full potential of LCNC platforms. Individual customers mostly see LCNC platforms as tools to realize hobby projects. Most of them lack the motivation to see a project through to completion.
The enterprise segment is not hobbled by such factors. The IT departments are full of people who can skillfully wield LCNC tools. This qualified workforce can establish guardrails and governance for non-technical LCNC users and slowly bring them into the fold. Additionally, the use cases in an enterprise environment are better defined compared to the individual segment. Employees know what they need to use an LCNC for and are motivated to invest time and effort in mastering these tools. Regular people with vague business ideas may struggle to figure out what they can do with such platforms. But these platforms become game changers in the hands of professional developers and domain experts.
Airtable was the first to make the pivot to the enterprise segment among no-code tools. Having achieved success through bottom-up adoption in big corporations, the company decided that a multi-pronged business strategy was not sustainable. As a result, management resolved to focus its efforts on the enterprise segment, where the upside looks more enticing than any other.
Another no-code platform, Bubble, also seems to be changing direction. Despite boasting a large user base and having raised large, Bubble's efforts to monetize its product weren't as successful. The company is now repositioning itself, targeting a piece of the ever-growing pie in the enterprise segment. This change comes as a surprise considering the popularity Bubble enjoyed among creative people and professionals with a side project.
2022 was a year during which organizations became more aware of their data integration problems. The SaaS sprawl, the explosive growth in unstructured data, and the ambition to make data-driven decisions have put data integration under the spotlight. Ensuring high data quality, breaking data silos, and finding the best data integration method for the needs of a business was on top of the agenda for people and organizations alike.
The challenge is to find the optimum combination of databases, data warehouses, and data lakes to satisfy specific data integration needs while balancing speed and operational costs. Terms like data fabric, data mesh, and logical data warehouse made the rounds throughout 2022 as the tech community sought to overcome this challenge. Just the discussion itself was enough to show that organizations of different sizes had data integration problems seeking urgent attention.
The enterprise segment for data integration tools is not without options as long as customers are willing to pay big bucks. However, SMBs and startups are devoid of any realistic solution, despite their growing data integration needs. Aware of this pain point, the Peaka team spent most of the year working on polishing the data integration capabilities of Peaka and unveiled the new Peaka at the end of October. Leveraging data virtualization technology, the new Peaka allows users to bring their data together without having to move or sync it. With our built-to-purpose data integration tool, SMBs and startups will be able to form a single view of truth in 2023 without employing expensive data teams or paying for costly enterprise-grade products.
2022 was a culmination point, with different trends coming together to signal a lasting change in the way hard tech is perceived by governments, entrepreneurs, and investors. It all started with the Covid-19 pandemic in 2020. The rush to develop vaccines highlighted the role biotech companies could play in times of crisis. Then came the supply chain issues in 2021, which particularly hit microchips hard, creating a squeeze in the supply of electronic devices and cars. In 2022, it was the Russian invasion of Ukraine that provided our yearly dose of chaos and uncertainty. The war brought energy prices to not-seen-before levels, with Russia proving that it couldn't be counted on as a reliable supplier of natural gas and oil. Green energy was a nice cause to root for prior to the war; now, it's a matter of sovereignty and industrial policy for governments.
Real-world problems are waiting for real solutions. It looks like stars are aligning for a new era where hard tech projects will become more prominent. Today microchip manufacturing, sustainable energy generation, biotech, automotive, defense, aviation, and space technologies are rejuvenated with a renewed interest and capital injection not seen in decades. It was the software industry and apps that pushed the frontier of technology in the last decade. 2022 might turn out to be an introduction to a new age of invention and innovation that will transform our lives.
AI was on a charm offensive throughout 2022. People flocked to create illustrations and artwork with OpenAI's Dall-E-2, got into conversations with the same company's AI-assisted chatbot ChatGPT at the end of the year, or whipped up avatars out of their photographs using the Lens app. Although not good for much other than having fun, the popular interest in these toys must have provided an enormous amount of data for these to train on.
However, we don't see a drastic increase in AI adoption rates in business just yet. According to an online survey McKinsey conducted among 1,492 participants, AI adoption has leveled off between 50 and 60 percent in 2022 despite having more than doubled since 2017. There seems to be a bottleneck here. AI is expected to decrease reliance on humans, but experienced engineering and data science talent capable of implementing AI projects are in short supply, which stops this particular technology from becoming mainstream. In the meantime, companies that have so far achieved high ROI for AI tend to invest in this technology significantly more than other companies and pull away from their competitors as a result.
Since there won't be a sudden increase in the supply of software engineers and data scientists any time soon, we will be counting on low-code/no-code platforms to pick up the slack and make AI accessible to the masses.
2022 was a hectic year for the tech industry and may prove to be a milestone when we look back at it some time in the 2030s. It may go down as the year LCNC platforms became staples in the corporate toolbox, data integration needs of SMBs and startups were recognized, hard tech startups took a leap forward, and AI attained public favor. It could have been just the perfect year if it weren't for the war.