CTOs face a big challenge: how to bring AI into their companies in a way that's safe, useful, and doesn't cause chaos. Enterprise search might be the answer they're looking for.

Enterprise search isn't just about finding files anymore. Modern systems can search through all kinds of company data - emails, chats, documents, code, and more. This makes them a great starting point for adding AI to your workplace.

How Enterprise Search Helps with AI Integration

CTOs often worry about integrating AI into their companies. It can seem complicated and risky, but platforms like enterprise search are perfect for making that integration easier. They solve many common AI problems without requiring major changes to how your company works.

Enterprise search is a great way to implement generative AI. It organizes all your company data, tools, and apps in one searchable place. 

Now that some enterprise search solutions use APIs to communicate directly with large LLMs (ChatGPT, Gemini, Claude), it gives employees a direct and easy way to use generative AI within their normal workflow, not as a separate tool.

Here are some ways enterprise search can make AI integration smoother:

Data access: AI needs data to work. Enterprise search gives AI a way to safely access company info without messing up your security.

Context understanding: Good enterprise search systems don't just find exact matches. They understand context, just like AI does. This helps AI make sense of your company's specific language and ideas.

Controlled rollout: You can start small by using AI with just the data in your enterprise search system. This lets you test things out before going bigger.

Existing workflows: People already use search at work. Adding AI features to search is less disruptive than bringing in totally new tools. Besides, most of the use-case scenarios of generative AI in the workplace include feeding the AI with data that employees search for.

Data governance: Enterprise search usually can incorporate rules about who can see what, and many of them can follow already existing security structures within the business. This helps keep AI use in line with your privacy and security policies.

Real-World AI Uses with Enterprise Search

A combination of enterprise search and generative AI can lift a lot of weight from CTOs shoulders. In their daily struggle to achieve optimal productivity, cut costs, and keep their companies competitive, they need a way to use new tech without causing any additional chaos. Smart search can help with all of this.

Enterprise search with AI can make teams work faster and smarter. It can find hidden knowledge in your company data, make onboarding easier, and help people make better decisions.

The best thing is that it does all this using data you already have. You're not starting from scratch or buying a whole new system. You're just making your existing info work harder for you.

Let's look at some practical ways CTOs can use AI with enterprise search:

Smart summaries: AI can read through search results and give quick summaries. This saves time when people are researching company topics.

Trendspotting: AI can analyze search patterns to find trending issues or growing areas of interest in your company.

Personalized results: AI can learn what's most useful for each employee and tailor search results to fit their needs.

Question answering: Instead of just showing results, AI can try to directly answer questions using info from your enterprise search index.

Code assistance: For tech teams, AI can use searched code to suggest improvements, find bugs, or explain how things work.

Meeting prep: AI can search through relevant docs and emails to create briefing notes before big meetings.

New hire onboarding: AI can create personalized learning paths for new employees based on their role and your company's searchable knowledge.

Things to Watch Out For

While enterprise search is a good way to start with AI, there are some things CTOs need to keep in mind:

Data quality: If your enterprise search data is messy or outdated, AI might give bad results. You'll need to clean things up.

User adoption: Make sure that the interface is intuitive and that AI features are actually helpful, or people won't use them.

Use guidelines: Set clear rules about how AI should and shouldn't be used with your company data. There are always risks of hallucinations and wrong data outputs that employees must be warned about, so defining a clear guideline on what tasks are best streamlined with AI and what should be avoided can be of great help.

Ongoing updates: Your company's language and knowledge will change. Make sure you have a plan to keep the data that is fed to AI up to date.

Getting Started

If you're a CTO thinking about AI, here's how to get going with enterprise search:

1. Audit your current search setup. Is it covering all your important data?
2. Talk to teams about their search frustrations. This will show where AI could help most.
3. Start small. Pick one AI use case, like summarization, and test it out.
4. Get feedback and adjust. See what works and what doesn't before expanding.

Ultimately, the enterprise search can be a very practical way for CTOs to bring AI into their companies. Because it uses systems that are already in place, works with existing data safety rules, and can be implemented quickly, enterprise search can become a right-hand assistant at every level of your company.

Enterprise search will ultimately be able to respond to all of the organization-related questions, automate various tasks that require intensive manual labor, create summaries, spot insights, and many other use-cases that allow employees to really extract the most value from business data.

If you are still not convinced, you can book a demo with Akooda and check out all of the latest enterprise search and generative AI features in action. 

It all happens quickly and easily through a one-click integration, and you can rest assured that it is all completely safe and up to the latest enterprise search security standards.

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