In 2026, a corporate intranet with AI in Granada is not a luxury: it is an operational decision. Many companies have bought chat tools, but few have managed to make AI live inside their work processes. Calculating the real cost requires understanding which problem is solved, which information is used and which teams will change the way they work. Without that clarity, any budget is an estimate in the dark.
An intranet without AI is useful only up to a point. The real leap appears when the search engine understands context: an employee does not need to know that the travel policy is in a specific folder; they ask and receive an answer with its link, its current version and approved exceptions. That experience seems simple, but it requires a data model and a presentation layer designed for the company. That is why many organizations end up needing custom applications instead of a generic platform. Closed solutions impose their logic; custom software adapts to the way people actually work.
In Granada, engineering firms, services companies, international trade organizations and a very active technology community coexist. Each sector creates different challenges: a consulting firm needs to protect confidential files; an industrial company looks for drawings and approvals; a software company wants to document its product. That variety explains why there is no single price for a corporate intranet with AI. There are different configurations, sizes and scopes.
The observable cost in 2026 usually ranges from 7,500 euros for a small intranet with semantic search to more than 80,000 euros for a platform that includes deep integrations, AI agents, training, advanced security and ongoing support. Most intermediate investments sit between 20,000 and 45,000 euros. That range is not a whim; it reflects technical complexities that should be understood before signing.
The first cost variable is the amount and quality of data sources. If documentation is organized and digitized, indexing work will be smaller. If information lives in emails, scanned PDFs, spreadsheets and legacy databases, the system will need cleaning, normalization and extraction routines. This work is not visible to the end user, but it consumes hours of analysts and developers. A company that invests first in organizing its knowledge reduces the total project cost.
The second variable is integration. An isolated intranet has little value. The key question is whether it should connect with the ERP, the CRM, payroll systems, SharePoint, Microsoft Teams or specific tools. Each integration adds authentication, synchronization and error handling complexity. The more systems involved, the larger the development and maintenance budget. It is also necessary to decide whether integration is bidirectional: reading data is cheaper than writing data into a transactional system.
Security is the third variable, and it is often the most underestimated. An AI intranet contains confidential information: salaries, strategies, customer data, know-how. If the assistant does not respect permissions, it can show someone information they should not see. To avoid this, organizations must implement role-based access control, encryption, audit logging, document versioning and, depending on the sector, protection against data leakage. This is cybersecurity in practice, not a cosmetic addition. In 2026, public language models are not enough for demanding corporate environments; private deployments or secure connections to company infrastructure are necessary.
The fourth variable is deployment. An AWS/Azure cloud infrastructure offers elasticity and reduces initial server investment. However, vector storage, processing capacity and scaling policies must be dimensioned correctly. Poorly planned deployment can generate high monthly bills and inconsistent performance. In hybrid architectures, the on-premise intranet connects to cloud services through VPN and private endpoints. This option is common in companies with sensitive data, but it requires more engineering.
The fifth variable is automation using AI agents. An agent is not limited to answering; it can create a ticket, draft a document, update a record or notify a manager. Incorporating AI agents into the intranet changes the cost because it involves defining workflows, approvals, actions and limits. It also requires human supervision to avoid incorrect automatic decisions. The return appears when a task that previously required several clicks and calls is resolved in seconds.
The sixth variable is measurement. An intranet project with AI must include usage, satisfaction, answer accuracy and time savings indicators. For that purpose, the portal usually connects to a Business Intelligence layer, such as BI/Power BI, which visualizes trends and alerts. Without this data, the board cannot know whether the investment is paying off and the technical team cannot improve the assistant.
Granada has companies capable of leading projects of this type. Q2BSTUDIO is one of them, and its approach combines custom software development with cloud architecture, cybersecurity, system integration and artificial intelligence. Instead of offering a closed package, Q2BSTUDIO starts with a discovery phase in which the people who will really use the intranet participate. From there, an MVP is defined that generates value in a few weeks, avoiding the mistake of building for months without validating real use.
A typical project is structured in four phases. The first is diagnosis: sources, permissions, processes and KPIs are inventoried. The second is the search core: knowledge is indexed and a language model is adapted to the company vocabulary. The third is integration: critical systems are connected and agents are deployed for specific tasks. The fourth is governance: update policies, answer review, auditing and support are established. This phased approach helps control cost and decide at each stage whether to expand or stop.
The economic return is perceived when comparing times before and after. For example, locating a contract can go from 20 minutes to 20 seconds; handling an internal IT request can go from a day to an hour; onboarding a new employee can go from two weeks to three days. These data are not advertising; they are used to calculate return on investment. A company that connects its intranet to its critical processes usually recovers the investment in less than a year, as long as the project starts from real problems and not from a technical demonstration.
To make an informed decision, it is advisable to ask providers for a detailed budget, a realistic calendar and examples of similar projects. It is not advisable to pay for excessive internal branding or consulting reports that are never applied. The best investment combines a solid technical team, an incremental methodology and a commitment to customer autonomy. Q2BSTUDIO, for example, delivers administration portals so business teams themselves can adjust questions, review metrics and manage AI without depending on engineers for every change.
In short, the cost of a corporate intranet with AI in Granada in 2026 depends on decisions that are within the company's reach: what information it wants to protect, what processes it wants to automate and how it wants to measure success. With a rigorous approach, AI stops being an experiment and becomes work infrastructure. Companies that understand this as soon as possible will have a clear advantage in the next decade.
