How Search AI Helps Improve Company Onboarding Process
With remote onboarding taking over the previously traditional corporate processes, today’s efficient onboarding needs 2 things: a centralized knowledge hub and an integrated enterprise search to navigate through it. Given that, new hires can learn truly productively as they discover necessary institutional knowledge almost immediately.
The same is valid for knowledge bases that serve customer onboarding. Providing newcomers with a comprehensive source of institutional knowledge is not enough – you must empower them with simple, instant, and actionable tips.
That’s why SaaS companies worldwide turn their eyes toward AI-powered search assistants. Let’s take a closer look at modern generative AI bots and how they boost the efficiency of user and trainee onboarding.
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Main Challenges of Using Decentralized Enterprise Knowledge Base for Onboarding
Most digital companies adopted a decentralized operation model to scale up their business processes. Doubtlessly, globally distributed teams allow businesses to get to the heart of local markets and process customer requests without time lag.
However, low-quality control is a recurring problem for such an operation mode. The assistant trainees might get stuck or misguided by unsupervised and poorly structured educational enterprise data. It frustrates both trainees and hiring supervisors, it eats up time and human resources, and eventually – it hurts business objectives.
So what are the culprits of this decreased productivity?
Data Silos
CIO analysts point out that about 80% of enterprise data is unstructured. The common enterprise knowledge is distributed across tens of applications and formats. This desperate allocation of necessary information leads to repetitive access requests, scrapping through Slack threads and Notion records, and other time-consuming fuss.
Troublesome Implementation of Metadata Indexing
Even though enterprise search can be improved through metadata tagging, it poses additional challenges. The dramatic growth of enterprise data volume complicates the implementation of scalable metadata tagging systems. The overlooked tagging inconsistency won’t let the system match necessary relevant data with keywords.
Misinterpreted Search Queries
Many keywords can express different meanings depending on the use context. Therefore, look-ups in the indexed data often yield broad results. The user has to pore through them meticulously or apply additional search filters.
Obviously, it’s a no-go approach if your company aims to increase the velocity of new hires or customer onboarding. The practice of search AI integration can offer a way out of this stalemate situation.
6 Benefits of Empowering Enterprise Knowledge Base with Generative AI
Incorporating AI technology into the onboarding process defies the limitations of traditional keyword searches. Generative AI chatbots outperform keyword-based crawlers when it comes to the accuracy and interpretation of a search intent.
But there’s more to it as AI search assistants deliver:
- Higher Search Relevance. AI bot understands user behavior by evaluating their search history and prediction algorithms. As a result, the user gets personalized search results that meet their expectations precisely.
- Genuinely User-Friendly Experience. Conversational GenAI bots engage users through natural and meaningful dialogue. The chatbot can grasp the meaning of questions and provide a rich context. For instance, it offersyou a timeline with documentation references if you ask, “What has been done about customer service ticket #15?”
- Systematization of Internal Knowledge. The ML algorithms recognize contextual interconnections between records and files stored in disparate applications. The data from Slack, Salesforce, GSuit, and other services will be automatically connected and logically categorized.
- No Additional Spend on Tagging. The deployment of AI-powered enterprises frees up tons of work hours and resources the company could spend on the tagging system and its maintenance. AI search is a cloud-based solution that doesn’t require supervision and additional computing power.
- Secure API Connection. The search AI systems transmit data through AES-256 encrypted API channels. It doesn’t require pre-indexing and sends API requests only upon user confirmation.
- Various Integrations. The AI-powered knowledge base can draw together internal data from diverse sources. Now, you’re just one click from discovering related information across Google Drive, Slack chats, or Asana projects. Moreover, you’re free to select custom integrations for case-specific use.
What Are the Business Outcomes of Integrating Search AI Products?
Simple and seamless onboarding for SaaS service customers and employees deserves more attention as it gets across the simple idea: business for people, not people for business. If you do recognize the value of positive experience and invest in it, then you’re on the right track to winning excellent customer and talent retention.
Engaging and deeply personalized onboarding lowers the entry threshold for customers. Besides, every person appreciates the feeling of accomplishment as they progress through onboarding. Thanks to AI prompts, customer progression becomes seamless, and churn rates get minuscule.
Talent onboarding, in turn, is about gaining expertise. The trainees are eager to learn fast and be ready to put new knowledge into practice. The shortcuts provided by AI search assistants remove the barrier to such endeavors, and training becomes sleek yet insightful. That’s a massive shot of encouragement to retain the new hires and nurture them into dedicated specialists.