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From Efficiency to Increase: How AI Fuels SME Growth

Updated: Apr 7



Plataforma de herramientas de Inteligencia Artificial para pequeñas y medianas empresas SumoPPM
SumoPPM Artificial Intelligence Platform for Businesses

Small and medium-sized enterprises (SMEs) that implement artificial intelligence experience productivity increases of 25% to 40% compared to those that do not use it, according to studies by McKinsey and Salesforce[1]. This differential is due to AI's ability to optimize processes, reduce operating costs and improve strategic decision-making.


Productive impact of AI on SMEs: How AI Fuels SME Growth

The impact of artificial intelligence on these companies can be seen in different areas:

  1. Process Optimization:

    • Automation of repetitive tasks such as invoicing or inventory management, which account for more than 50% of employee time[2].This frees up employees to focus on higher-value and more creative tasks.

    • 30% reduction in operational errors thanks to predictive monitoring[3]. This helps companies grow and reduce their costs.

  2. Commercial Efficiency:

    • 30% increase in sales conversion through hyper-personalized marketing campaigns, as well as a significant increase in sales[4].

    • Reduction in wait times and customer service with chatbots[5].

  3. Predictive Management:

    • Exponential improvement in the accuracy of demand and purchasing forecasts[6]. This use of AI fuels SME growth abundantly.


Key AI Tools for SMEs

AREA

TOOLS

IMPACT

Customer Service

Chatbots

24/7 support, improved response times, and a 30% reduction in customer service costs[7]

Data Analysis

Generative BI and AI data analysis tools

Decision-making based on predictive patterns. Identifying business opportunities accurately[8]

Marketing

Virtual Assistants (AI agents), audience segmentation tools

Increased advertising ROI, lead generation, and network management[9]

Financial management

AI CRM, AI ERP

50% automation in accounting processes[10]

Predictive AI

SumoPPM models for inventory and demand analysis

Reduction in out-of-stocks and improved cash flow


Reasons for adoption

  1. Competitiveness: 83% of Spanish SMEs that use AI report increased revenue[11].

  2. Sustainability: Reduction in operating costs through resource optimization and error reduction[12].

  3. Adaptability: Ability to process big data and adapt to changing markets[13].

  4. Customer experience: Personalization of services through behavioral analysis[14].


Specific benefits of SumoPPM for SMEs

This platform, created with artificial intelligence at its core and to make this new technology available to businesses, using its own blockchain, offers significant advantages in terms of data security and reliability. SumoChain replicates the information on different servers, which ensures that the data remains intact and reduces the risk of errors. The private architecture and advanced encryption protect the information against tampering and ensure that only authorised persons can access it.


Handles large volumes of transactions and data without compromising security or performance. Data is protected and isolated: AI models run within our infrastructure, without sharing information with third parties.


SumoPPM artificial intelligence tools give small and medium-sized businesses a competitive advantage by combining intelligent automation, continuous availability and predictive analytics. The platform has seven AI tools specifically designed to help businesses: virtual assistants (AI agents), tool connector, audio analytics, chatbots, data analytics, web data mining and predictive modelling. These include:


Chatbots and virtual assistants:

Its chatbots, available 24 by 7, manage queries, schedule appointments and close sales without human intervention, reducing operating costs by up to 30%, while virtual assistants free staff from repetitive tasks such as managing emails or analysing calls, allowing them to redirect resources towards growth strategies.


Their capacity to integrate with tools such as Shopify and WhatsApp to close sales automatically[15], stands out, as does the 30% reduction in customer response times[16].

 

Tool connector and data analysis:

Achieves automation of workflows between systems (e.g. ERP-CRM data synchronisation)[17]. Integration with existing business systems or other tools simplifies decision-making, offering immediate scalability and a seamless customer experience.


Predictive models, which can be trained on your own data without programming, transform historical data into accurate forecasts to optimise inventories, forecast market trends and personalise offers, increasing efficiency by up to 40%.[18].


SumoPPM is positioned as a revolutionary solution for SMEs, democratising advanced data analysis through generative artificial intelligence (GenAI) and blockchain. This tool allows you to create customized dashboards with more than 50 types of graphs through written conversation with SumoPPM, eliminating the need for technical knowledge and reducing costs in specialized training[19].


Real-time visualisation and customisable machine learning models (FlexiModel) deliver actionable insights to optimise everything from sales to operational management, turning raw data into sustainable competitive advantage.


Furthermore, its blockchain technology ensures maximum data security and integrity, while AI capabilities automate complex tasks such as trend detection and forecasting, speeding up strategic decision-making by up to 70%.


Conclusion:

AI is no longer an option but a strategic requirement: 75% of SMEs globally are already using or experimenting with it, and its adoption is growing by 8% annually among companies with more than 10 employees from 2023 according to EU data[20]. Platforms such as SumoPPM democratise access to these technologies, offering scalable solutions that match the capabilities of large corporations. The use of Artificial Intelligence in SMEs increases their productivity, competitiveness and growth.



Notes:

[1] (Chui, y otros 2023); (PKM 2024).

[2] (Chui, y otros 2023).

[3] (Ai Verso y el Instituto Alemán de Cooperación e Innovación 2023);  (Calle, y otros 2024)

[4] (Chui, y otros 2023); (Reason Why 2024); (Jensen 2025). 

[5] (Das, y otros 2023); (Redask 2025).

[6] (Amosu, y otros 2024).

[7]  (Acelera Pyme 2022); (Jobanputra 2024).

[8] (Institute of Data 2023).

[9] (Calle, y otros 2024)

[10] (Basomba 2025) 

[11] (PKM 2024) 

[12] (PKM 2025); (Ocaña Olivares 2025); (Cortés Ricart 2025) 

[13] (Calle, y otros 2024)

[14] (Calle, y otros 2024); (Cortés Ricart 2025) 

[15] (SumoPPM 2025)

[16] (SumoPPM 2025)

[17] (SumoPPM 2025)

[18] (Torrego 2024)

[19] (Torrego 2024)

[20] (PKM 2024); (Eurostat 2025).


Sources

Acelera Pyme. 2022. «Acelera Pyme.» Inteligencia artificial para pymes. 22 de diciembre. Último acceso: 20 de marzo de 2025. https://www.acelerapyme.gob.es/novedades/infografia/inteligencia-artificial-para-pymes.

Ai Verso y el Instituto Alemán de Cooperación e Innovación. 2023. «Ai Verso.» Cómo Reducir Errores Humanos con la Implementación de la IA en la empresa. 3 de noviembre. Último acceso: 20 de marzo de 2025. https://aiverso.com/como-reducir-errores-humanos-con-la-implementacion-de-la-ia-en-la-empresa/#Estudio_de_Caso_1_Automatizacion_de_Procesos.

Amosu, Olamide Raimat, Praveen Kumar, Yewande Mariam Ogunsuji, y Segun Oni y Oladapo Faworaja. 2024. «AI-driven demand forecasting: Enhancing inventory management and customer satisfaction.» World Journal of Advanced Research and Reviews 2 (23): 708–719.

Basomba, Marc. 2025. «KPMG.» Tendencias. 26 de febrero. Último acceso: 22 de marzo de 2025. https://www.tendencias.kpmg.es/2025/02/transformacion-contabilidad-era-inteligencia-artificial/.

Calle García, Aldrin Jefferson, Marolen Ciare Quimis Vera, y Mayerli Tatiana y Zambrano Luzardo, Jostin Steven Piguave Vargas. 2024. «La inteligencia artificial como herramienta en la segmentación de mercado.» Editado por Universidad Alas Peruanas. Ciencia y Desarrollo 1 (27): 193-202.

Chui, Michael, Eric Hazan, Roger Roberts, Alex Singla, Kate Smaje, Alex Sukharevsky, y Lareina y Zemmel, Rodney. Yee. 2023. «McKinsey Digital.» The economic potential of generative AI: The next productivity frontier. 14 de junio. Último acceso: 20 de marzo de 2025. https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier#key-insights.

Cortés Ricart, Marc. 2025. «ESADE.» Beyond by ESADE. 2 de enero. Último acceso: 22 de marzo de 2025. https://www.esade.edu/beyond/es/ventajas-retos-inteligencia-artificial-empresas/.

Das, Avinash Chandra, Greg Phalin, Ishwar Lal Patidar, Malcolm Gomes, y Rakshit y Thomas, Renny. Sawhney. 2023. «McKinsey & Company.» Capabilities. 27 de marzo. Último acceso: 20 de marzo de 2025. https://www.mckinsey.com/capabilities/operations/our-insights/the-next-frontier-of-customer-engagement-ai-enabled-customer-service.

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Ocaña Olivares, Javier. 2025. «Telefónica.» Sala de Comunicación. 25 de febrero. Último acceso: 22 de marzo de 2025. https://www.telefonica.com/es/sala-comunicacion/blog/inteligencia-artificial-cambiar-mundo-empresarial/.

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—. 2025. SumoPPM. febrero. Último acceso: 22 de marzo de 2025. https://www.sumoppm.com/chatbots.

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