Canonical URL: https://elacelerador.es/en/data-and-automation/omega-crm-astra-commercial-ai/ --- description: The June 24 announcement describes five maturity levels and an AI readiness assessment. Its aggregated improvement claims identify no customers or method. title: Omega CRM introduces astra and a two-week AI maturity assessment image: https://elacelerador.es/images/social/v1/omega-crm-introduces-astra-two-week-ai-maturity-assessment-f893b2b91cf615c3ae6c01e651627aeb.jpg --- 1. [Home](https://elacelerador.es/en/) 2. [Data and automation](https://elacelerador.es/en/data-and-automation/) # Omega CRM introduces astra and a two-week AI maturity assessment The June 24 announcement describes five maturity levels and an AI readiness assessment. Its aggregated improvement claims identify no customers or method. By [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 13 October 2026 at 00:12 CEST 5 min read [ Add as preferred source ](https://www.google.com/preferences/source?q=elacelerador.es&utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) Share [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Felacelerador.es%2Fen%2Fdata-and-automation%2Fomega-crm-astra-commercial-ai%2F%3Futm%5Fsource%3Dlinkedin%26utm%5Fmedium%3Dsocial&utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es "Share on LinkedIn. 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Preview requests: 0") ![Person reviewing charts on a tablet](https://elacelerador.es/images/variants/v1/omega-crm-introduces-astra-move-commercial-ai-beyond-pilots-person-reviewing-charts-w1280.webp) Charts on a tablet. Archive photograph illustrating work with business data. Framing adapted. Photo: [PXHERE · CC0](https://commons.wikimedia.org/wiki/File:Business%5Fman%5Fwith%5Fgraph%5Fchart%5Fon%5FiPad.jpg?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) [Omega CRM](https://elacelerador.es/en/company/omega-crm/) offers a two-week assessment to decide where AI belongs in commercial work. The period refers to a diagnosis, rather than achieving the consultancy’s reported savings within a fortnight. Astra’s economic decision is identifying a task whose outcome can improve, together with the work required to bring that improvement to the customer. The June 24, 2026 announcement cites reductions of up to 33.7% in operational handling time, approximately 15% in operating and service costs, and productivity increases exceeding 12%. It attributes them to implementations in sectors including property and food distribution without identifying businesses, periods or samples. These are provider claims about different measures, which cannot be added or establish the outcome of purchasing astra. ## Using a tool does not establish process maturity Astra places five levels between manual processes with disconnected data and agent ecosystems collaborating with people to execute complex processes. The notice supplies no complete matrix for reproducing each classification. The AI Readiness Assessment proposes examining the organisation, prioritising use cases and preparing a roadmap. That structured decision is the deliverable, preceding implementation and its outcomes. Different work environments help explain the limit of a technology label. Among 100 Spanish technology and business leaders surveyed by Deloitte from July to September 2024, 60% reported productivity tools and 49% corporate platforms, according to Statista. The survey selected organisations already using AI daily and running generative-AI pilots or implementations. It does not estimate adoption across all Spanish companies. The data behind the story ### Deloitte Spain: AI appears in different work environments 100 technology and business leaders in Spain, July–September 2024\. Organizations using AI daily and running generative-AI projects. Reported use Tap or hover for details. All values are also available in the data table. Expand notesCollapse notes **Sources:** Statista; Deloitte Spain: original five use-case values; Deloitte Q4 2024: global sample and eligibility, Nordic cut methodology, p. 29 Deloitte / Statista. Selected leaders at organizations using AI daily and running generative-AI pilots or daily implementations, rather than all Spanish businesses. Uses overlap and must not be added. Original methodology, p. 29, confirms eligibility. This does not measure savings, output quality or the analyzed provider’s customers. Explore the data table Scroll left or right to see all columns __Deloitte Spain: AI appears in different work environments (%)__ | Category | Reported use | | -------------------------- | ------------ | | Public language models | 62.0% | | Productivity tools | 60.0% | | Generative AI applications | 56.0% | | Corporate platforms | 49.0% | | Code generation | 31.0% | Drafting a reply and acting on a commercial record create different dependencies. The former can end in a proposal; the latter needs current information, authority and a state supporting continuation. An assessment needs to explain which action will change and who receives its outcome. A licence or model availability does not establish that the team can use the result without rebuilding context. INE estimated AI use among 21.1% of firms with ten or more employees in the surveyed sectors in Q1 2025, using approximately 15,000 firms stratified by size, activity and region. Its population and question differ from Deloitte: technology use rather than astra maturity. Subtracting the percentages would produce an uninterpretable difference. ## Prepared information needs to serve the next step Omega identifies prioritisation, data readiness and internal adoption as difficulties. Its property example describes agents recommending developments, arranging viewings and following up. The notice attributes completed sales to that assistance without case records isolating its contribution. The sequence does identify three different commitments: a valid option, a confirmed appointment and a buyer’s decision. The Ascend2 survey reported by Statista supplies a marketing reference: 61% of 374 respondents cited customer experience among the greatest benefits of improving data, 35% lead generation and 15% team alignment. These are perceived benefits in January 2023, rather than measured AI improvements. The panel mixes B2B and B2C and does not specify geography. The comparison separates tasks an assessment needs to examine independently. The data behind the story ### Data quality is linked to different customer-relationship tasks Areas where marketing decision-makers report the greatest benefits, January 2023. Benefit cited Tap or hover for details. All values are also available in the data table. Expand notesCollapse notes **Sources:** Statista; Original source Ascend2: online survey January 16–22, 2023, n=374, multiple answers. The panel includes B2B (20%), B2C (52%) and mixed (28%) companies. These are reported benefits, not measured lift or causal evidence; the original report does not specify geography. Explore the data table Scroll left or right to see all columns __Data quality is linked to different customer-relationship tasks (%)__ | Category | Benefit cited | | ------------------- | ------------- | | Customer experience | 61% | | Engagement | 45% | | Lead generation | 35% | | Personalization | 34% | | Decision-making | 33% | | Email marketing | 29% | | Team alignment | 15% | A development can remain in the CRM while its availability changes. A suggested appointment may not yet exist in the calendar. A completed viewing can leave an objection the next message needs to recognise. At each boundary, data readiness means preserving the promise and establishing what can now be executed. Accelerating a reply that hands over incompatible work moves effort into sales or service. An assessment can therefore use a concrete investment criterion: choose a stage whose outcome can be completed with available information and responsibilities. Diagnosis does not remove the cost of maintaining data or handling exceptions. A roadmap needs to retain that subsequent work alongside initial development, so the purchase does not end in an unsupported capability. ## Time, cost and resolution retain their denominators Faster handling can release time without lowering payments for shifts, contracts or systems. It can also help serve demand already waiting. Neither outcome automatically means additional sales. Interpreting Omega’s percentages requires the task, period, included costs and counted outcome; placing the three numbers together does not supply a common base. Brynjolfsson, Li and Raymond supply another definition in Generative AI at Work, published in 2025: using 5,172 support agents, they estimated a 15% average increase in issues resolved per hour after a staggered rollout. The setting is support for a software company, with most agents outside the US, mainly in the Philippines. This is neither an astra result nor a forecast for Spain. The reference earns its value by naming output and its time unit. A useful recommendation still needs to reach the team scheduling or negotiating. If that receiver has to find the information again, some apparent saving reappears. If the team can continue from the correct state, released capacity can reduce waiting or absorb additional work. Economic observation follows through to that point, identifying interventions and demand changes, rather than ending when the assistant replies. The two-week assessment offers a way to choose the next commitment. For Omega, the test is whether each priority connects usable data, an action and an outcome the business can recognise. A recovered minute is worth what it enables afterward. Astra’s commercial argument becomes more defensible when its roadmap explains that continuity as well as the assigned maturity level. ## In this article ### Companies * [Omega CRM](https://elacelerador.es/en/company/omega-crm/) ### Sources and documents * [Omega CRM: June 24, 2026 announcement](https://omegacrmconsulting.com/conoce-astra-by-omega-crm/?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · Omega CRM * [Omega CRM: legal identity](https://omegacrmconsulting.com/aviso-legal/?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · Omega CRM * [Dentsu: Omega CRM origin and acquisition](https://www.group.dentsu.com/en/news/release/000914.html?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · Dentsu * [ICT and AI use in companies Q1 2025](https://www.ine.es/dyngs/Prensa/ETICCE20241T2025.htm?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · INE * [Generative AI at Work, published QJE 2025, author-hosted full text](https://danielle-li.github.io/assets/docs/GenerativeAIatWork.pdf?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · Brynjolfsson, Li and Raymond / Quarterly Journal of Economics * Statista * [Deloitte Spain: original five use-case values](https://www.deloitte.com/es/es/services/consulting/research/estado-ia-generativa-empresas-espana.html?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · www.deloitte.com * [Deloitte Q4 2024: global sample and eligibility, Nordic cut methodology, p. 29](https://mkto.deloitte.com/rs/712-CNF-326/images/state-of-gen-ai-nordic-cut-q4.pdf?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · mkto.deloitte.com * [Original source](https://ascend2.com/wp-content/uploads/2023/02/Outlook-on-Marketing-Data-Quality-230119.pdf?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) · ascend2.com Share [ ](https://www.linkedin.com/sharing/share-offsite/?url=https%3A%2F%2Felacelerador.es%2Fen%2Fdata-and-automation%2Fomega-crm-astra-commercial-ai%2F%3Futm%5Fsource%3Dlinkedin%26utm%5Fmedium%3Dsocial&utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es "Share on LinkedIn. 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Preview requests: 0") ![Portrait of Marian Vasile](https://elacelerador.es/images/variants/v1/marian-vasile-autor-acelerador-retrato-w320.webp) [LinkedIn](https://www.linkedin.com/in/nairamelisav/?utm%5Fsource=elacelerador.es&utm%5Fcampaign=elacelerador.es) About the author ## [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) Marian Vasile is a MarTech and growth professional. His work spans product marketing, SEO, paid advertising and deep online tracking, including behavioral analytics and attribution. ## Related articles [Data and automation](https://elacelerador.es/en/data-and-automation/) Analysis ### [Automate marketing with clear accountability](https://elacelerador.es/en/data-and-automation/automate-marketing-with-clear-accountability/) [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 13 October 2026 5 min [Data and automation](https://elacelerador.es/en/data-and-automation/) Analysis ### [Reduce the effort of joining a platform](https://elacelerador.es/en/data-and-automation/reduce-the-effort-of-joining-a-platform/) [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 13 October 2026 5 min [Data and automation](https://elacelerador.es/en/data-and-automation/) Analysis ### [Connect campaigns, product and revenue](https://elacelerador.es/en/data-and-automation/connect-campaigns-product-revenue/) [Marian Vasile](https://elacelerador.es/en/author/marian-vasile/) 13 October 2026 5 min ```json {"@context":"https://schema.org","@graph":[{"@type":["Organization","NewsMediaOrganization"],"@id":"https://elacelerador.es/#publisher","name":"El Acelerador","url":"https://elacelerador.es/","description":"Marketing and growth hacking with examples from Spanish companies.","email":"pr@elacelerador.es","publishingPrinciples":"https://elacelerador.es/en/editorial-policy/","correctionsPolicy":"https://elacelerador.es/en/editorial-policy/","verificationFactCheckingPolicy":"https://elacelerador.es/en/editorial-policy/","masthead":"https://elacelerador.es/en/about/","ownershipFundingInfo":"https://elacelerador.es/en/about/","logo":{"@type":"ImageObject","url":"https://elacelerador.es/icon-512.png?v=20261017-stacked"}},{"@type":"Person","@id":"https://elacelerador.es/author/marian-vasile/#person","name":"Marian Vasile","url":"https://elacelerador.es/en/author/marian-vasile/","description":"Marian Vasile is a MarTech and growth professional. 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