7 Predictions for Insight Apps and the Future of Search


The advent of Natural Language Understanding (NLU) with Neural Search will open up new possibilities in enterprise search.

After 2021, marked by disruption and digital transformation at a scale not previously imagined, we look to a new year and the top trends and opportunities for strategic growth. With digital workplace transformation taking precedence among business priorities, enterprise search is an unsung hero in the modern way of work.

Here are seven trends – and predictions – shaping the future of work and how enterprise search impacts digital transformation strategies in 2022 and beyond:

1. Natural Language Understanding comes to the forefront: Search technology to date has primarily been focused on counting words and statistical analysis of word forms, enhanced by Natural Language Processing. The advent of large language models (such as Google’s BERT) changed that – bringing Natural Language Understanding to web search. But its complexity and need for computing power have kept these advances out of enterprise search until now. Advances in Neural Search and applying this technology efficiently for corporate environments will come to the forefront and transform the enterprise search experience by bringing an unprecedented level of accuracy and contextual relevance by understanding meaning.

Prediction: Like any “new” technology, expect incremental adoption in early 2022, with Neural Search capabilities accelerating from a nice-to-have to absolutely essential over the course of the year. Expect a tremendous amount of market noise…and confusion…around this topic as providers struggle to deliver and customers grapple to apply NLU.

2. Resurgence of Knowledge Management: Although the idea has been around for half a century, waxing and waning in popularity and priority, Knowledge Management has taken on new focus with the rapid push to remote work. It will continue an assertive resurgence in 2022 as it makes its way higher on the CEO’s agenda to ensure workers have the information they need to drive the business. The cause of this resurgence is a confluence of factors, including the ongoing global pandemic, forcing unprecedented changes to the way we work – as well as the proliferation of data and applications increased consumer and employee expectations. Then there is ‘The Great Resignation,’ where many people have tasted or envisioned a different kind of work. This makes KM important in three ways: 1. making employees’ jobs easier increases retention; 2. accessing knowledge irrespective of work location makes hybrid work models easier; and 3. it protects against the loss of institutional knowledge for people who do leave. For all of these reasons, Knowledge Management is a strategic imperative for 2022 and beyond. 

Prediction: Expect to see large enterprises elevate and increase leadership KM positions such as chief knowledge officers (CKO) and chief learning officers (CLO), while chief digital officer titles become table stakes. Post-pandemic, most businesses are digital businesses.

3. Organizational Intelligence emerges from the KM revival: With the KM revival comes new meaning and maturity, marked by a shift from information management and control to augmented human intelligence. CEOs realize that people, information, and skills are a company’s most valued resources. They realize that the future of business rests on how the collective knowledge within an organization is acquired, organized, shared, preserved, applied, and advanced. All of these spokes are key to the information hub, but especially how it is applied (that’s where the value of knowledge is realized) and advanced (that’s how a company beats the competition) are critical components – and companies need better ways to harness that knowledge dynamically and organically.

Prediction:  2022 will be the year the word “Intelligence” shapes all digital initiatives. Specifically, fostering collaboration through Organizational Intelligence and augmenting human decision-making with new Decision Intelligence tools – powered by machine learning, AI, and deep learning – come to the forefront.

4. Application splintering reaches epidemic status; Search closes in on cure: On average, employees must use 35 job-critical applications every day! This application splintering creates a very real human toll from application switching, bookmark scattering, and the cognitive burden required to create some sort of “flow” amid so many disconnected systems. The big players have realized this and are trying to consolidate the digital chaos with an ecosystem (e.g., Microsoft Teams), but a unified workspace isn’t possible without a consistent way of accessing content and harnessing knowledge from the entire enterprise. Comprehensive search – at the corporate level, not the ecosystem level – is the only way to bring clarity to the chaos, reduce task switching, and redirect that cognitive burden to gaining insights and value within the flow of work.

Prediction: Productivity gains from specialized apps are undisputed, so expect app splintering to continue, with firms experimenting with a variety of possible solutions (consolidation, training, custom integration, search) and search becoming perhaps the only proven way for employees to seamlessly interact with knowledge.

5. The search paradigm changes from pull to push Highly skilled digital workers must use their knowledge to decide and act in the flow of their work to drive the business. However, there is too much to know, and knowledge decays – thus, they must rely on the ability to find information. As stated in a recent Gartner research, executive leaders need to help their colleagues leverage emerging technologies that dynamically and proactively surface information in the flow of work for a continuously informed workforce. Custom Insight Applications that leverage the power of relevance turn search on its head, bringing up pertinent and helpful insights as employees do their work – without the need to step out of the flow and perform a search.

Prediction: Knowledge-first enterprises are starting to change the paradigm from “pull” (go look for it) to “push” (proactively surfacing insights) and doing so right when the employee needs it. 2022 will bring an increased focus on leveraging the sophisticated relevance of search without the actual “search,” leveraging the power of AI and Neural Search, so that knowledge finds employees.

6. Specialized Low/No-Code Search-Based Insight Apps bring more value: Unlike other search contexts, finding content in the enterprise is not one-size-fits-all. The demands of unique and complex knowledge work, such as innovation, can only be met with specialized Insight Apps. The advent of no-code and low-code frameworks means that companies can now deploy many Insight Apps for specialized use cases quickly and without developers.

Customized search experiences have not been quick to develop and deploy nor easy to maintain, limiting the number of Insight Apps and forcing some employees to use unoptimized solutions – or go without. Low- and no-code frameworks and development tools mean fast customization without expensive developers and greatly reduced operating costs. This translates to more search being used by more employees in more contexts, bringing improvements to the work experience for more workers and more use cases.

Prediction: The average number of use cases – and corresponding custom Insight Apps – will increase as companies take advantage of low/no-code platforms to quickly address the needs of more workers. Point solutions based on a narrow application of search will no longer be practical; the most value and the highest ROI will come from platforms that can leverage the relevance of search for multiple use cases with a single product.

7. Cloud powers the neural search revolution. Cloud adoption continues, but it is no longer a strategy unto itself. It’s time to leverage the power of the cloud for benefits not possible with on-premise deployments. This is particularly true as applications for AI become real, as the cloud is well-suited for the computing demands of neural search, large scale, and advanced applications such as speech-to-text and translation. But it’s not as simple as just saying “cloud” and done. The intense demands of these sophisticated techniques require optimization to minimize the computing cost and be green.

Prediction: Companies start to leverage the computing power of the cloud to accomplish new feats – AI, the NLU of Neural Search, and the high flexibility afforded by the high elasticity of the cloud. Tech platforms must optimize for the different cloud providers so that cloud-based customers can fully leverage these capabilities, particularly as climate change becomes more of a focus due to both culture and regulatory pressures.

With the pace of digital change in business showing no sign of slowing in 2022, the future of enterprise search is bright. Two huge forces will transform how we work with knowledge in 2022. The advent of NLU with Neural Search will open up new possibilities, right as the push for better knowledge management in the “new normal” – distributed, hybrid, asynchronous workplaces – demands that we do better. Fortunately, intelligent search platforms are up to the task, giving enterprises the power to surface better insights from the search bar – but also to proactively push relevant knowledge into the flow of work.

Jeff Evernham

About Jeff Evernham

Jeff Evernham is Vice President of Product Strategy at enterprise search provider, Sinequa. His 30-year career spans data analytics consulting, professional services, sales, and engineering roles at multiple software and management consulting firms. He holds a Master of Engineering degree from MIT. He can be reached at https://www.linkedin.com/in/jeffevernham/.

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