Until recently, generative artificial intelligence seemed to be the privilege of large corporations. Today, it has become a key tool for small and medium-sized enterprises (SME's) to automate tasks, customize services and reduce costsThe company is able to compete even with limited resources.
Key data on its impact:
- The 70% of Argentine SMEs The company already considers it fundamental to improving its competitiveness.
- The most used applications include automated customer service, content generation and internal process optimization.
- The 89% for companies manages to implement it in less than 12 months, accelerating its digital transformation.
- Main challengesOvercoming distrust in technology and strengthening team training. with clear objectives and measurement of results.
To take advantage of its full potential, it is necessary to define a clear strategy, with measurable objectives and a practical approach.
Introduction to Generative AI for Enterprises
Generative artificial intelligence (GAI) is transforming the way companies create and optimize their work. Unlike other types of AI, which focus on analyzing data and making predictions, this technology can generate text, images, code and even music.
What was once only available to large companies is now an accessible tool for small and medium-sized enterprises. Thanks to platforms designed for practical use, more and more businesses are incorporating IAG to automate processes and improve their customers' experience.
In addition to saving time on repetitive tasks, this technology opens up new possibilities for innovation and differentiation in competitive markets.
The impact of Generative AI in Argentine SMEs
Unstoppable growth
More and more companies in Argentina are betting on generative artificial intelligence. According to Microsoft, 70% of SMEs already see it as an essential tool to improve their competitiveness and customer experience. In addition, 67% plan to invest in this technology in the next year, reflecting its growing adoption.
This expansion responds to two key factors: the access to more affordable tools and the need to optimize processes in a challenging economic context. For many SMEs, the IAG represents an efficient way of improve your operation without requiring large investments in personnel or infrastructure.
Main use cases
The flexibility of this technology allows it to be applied in different aspects of the business. Some of its most common implementations include:
- Customer serviceChatbots that answer queries in real time, improve user experience and optimize costs without losing proximity.
- Content generationCopywriting for marketing, social media and internal communications, tailored to each audience.
- Process automationOptimization of repetitive tasks, data analysis and report generation without manual intervention.
- Research and developmentSupport in the generation of ideas and creative solutions for products or services.
- Predictive analyticsIdentification of market trends and consumer behavior to make better decisions.
These applications can be combined to further enhance the impact of generative AI in each enterprise.
What generative AI brings to SMEs
Adopting this technology not only improves productivity, but also opens up new opportunities for growth. Some of its most outstanding benefits include:
- Increased efficiency → Automate repetitive tasks, allowing teams to focus on strategic activities. Tools like IBM's Watsonx are already helping to streamline administrative processes.
- Customization at no extra cost → Tailor products, services and communications according to each customer's preferences without the need for large investments.
- Savings in operating costs → Companies that have implemented these solutions report up to a 30% reduction in expenses in areas such as marketing, customer service and administrative management.
- Access to world-class technology → What was once exclusive to large companies is now available to any business that wants to innovate and compete on a level playing field.
- Boosting creativity and innovation → Facilitates the generation and testing of new ideas, accelerating the development of products and services.
In a challenging market like Argentina's, optimizing resources and differentiating yourself is more important than ever. Generative AI is not just a tool, but an opportunity to evolve and grow.
How to implement generative AI effectively
Define specific objectives
The first step is to set clear and measurable goals. Instead of a general approach such as "use generative AI", it is more useful to set specific goals, such as "reduce customer service response time using chatbots by 40% in the next three months.". This makes it possible to evaluate the real impact of the technology and adjust the strategy according to the results.
Choosing the right tools
Not every AI solution will fit every business. The selection should be based on the actual needs of the company, the budget and the team's ability to integrate and manage the technology. Some popular choices among Argentine SMEs include:
| Tool | Main use case | Complexity | Pricing model |
|---|---|---|---|
| ChatGPT (OpenAI) | Content generation, customer service | Low-Medium | Freemium/Subscription |
| Watsonx (IBM) | Process automation, data analysis | Medium-High | Subscription/Use |
| Microsoft Copilot | Productivity, task assistance | Low-Medium | Subscription |
| Google Gemini | Research, content generation | Under | Freemium/Subscription |
| Midjourney | Image generation and design | Under | Subscription |
It is advisable to start with tools that offer intuitive interfaces and do not require advanced technical knowledge, allowing for gradual adoption as the team develops competencies.
Preparing the team to take advantage of generative AI
The real impact of this technology depends on those who use it. Training the team not only improves adoption, but also optimizes results. Training should include:
- Basic concepts → How generative models work and in which cases to apply them.
- Practical use → Training on the chosen platforms to maximize your potential.
- Effective Prompts → Techniques for giving clear instructions and getting better answers.
- Evaluation and adjustment → Criteria for reviewing, correcting and improving the content generated.
- Ethical aspects → Bias, reliability and responsible use of AI considerations.
Many SMEs are already taking advantage of training offered by the government, universities and technology companies. Programs such as AI for SME Productivity provide specific training for this sector.
Efficient data management
The effectiveness of generative AI depends on the quality of the information it works with. To optimize its performance, SMEs can apply good data management practices, such as:
- Efficient organization → Keep data classified and easily accessible.
- Cleanliness and consistency → Ensure that the information is accurate and error-free.
- Security and privacy → Protect sensitive data with appropriate protocols.
- Constant updating → Keep information up to date to improve AI accuracy.
- Relevant context → Feed the models with business-specific information.
There is no need to invest in complex infrastructure. Simple tools, such as well-structured spreadsheets, can be an effective solution for many SMEs.
Partnering with experts
Not all SMEs have specialized technology teams, but that is not an obstacle to adopting generative AI. Collaborating with external experts can speed up the process and optimize results. Some options include:
- Specialized consultants → Professionals who design tailor-made strategies according to the needs of the business.
- Solution Providers → Companies that offer tools adapted to different sectors.
- Communities of practice → Spaces to share experiences and learn from other success stories.
- Academic institutions → Universities providing access to research and training in technology.
- Accelerators and incubators → Programs that connect companies with mentorships and key resources.
In Argentina, consulting firms such as KOLT help SMEs implement advanced digital solutions, including generative AI, with a practical approach aligned with the local context.
Best Practices
Agility in adoption
The speed with which a company implements generative AI directly influences its impact. 89% of Argentine companies that have adopted this technology have done so in less than a year, demonstrating that moving forward with a clear strategy is key to success.
To accelerate the implementation, our consultant KOLT recommends:
- Start with pilot projects of controlled range.
- Use agile methodologies with short test and adjustment cycles.
- Prioritize tools that do not require complex integrations at the beginning.
- Establish channels of feedback to optimize results.
- Document and good practices for future improvements.
Responsible and ethical use
Adopting generative AI with ethical criteria not only avoids risks, but also strengthens the trust of clients and collaborators. Some essential practices include:
- Transparency → Report when AI-generated content is used.
- Human supervision → Maintain control over critical decisions.
- Data protection → Ensure the privacy of the information used.
- Respect for intellectual property → Avoid plagiarism and acknowledge sources.
- Bias minimization → Review results to ensure equity.
Iterative and scalable approach
The implementation of generative AI should not be seen as a project with an end point, but as a a constantly evolving process. An iterative approach allows:
- Adjust strategies based on experience and results obtained.
- Gradually expand the use of AI from basic applications to more advanced solutions.
- Adapt to technological changes and new opportunities.
- Incorporate feedback from users and customers to improve the experience.
- Maximize return on investment with continuous optimizations.
Companies that follow this approach not only obtain better results in the short term, but also develop a greater capacity to adapt over time.
Challenges and considerations in the adoption of generative AI
Regulation and compliance
The legal framework around generative AI continues to evolve, creating uncertainty for companies looking to adopt it. Some aspects to keep in mind are:
- Regulations under development → Lack of specific regulations may hinder legal compliance.
- Responsibility for content → Defining who is accountable for what is generated by AI is still an open debate.
- Data protection → Compliance with the Personal Data Protection Act and other local regulations.
- Copyrights → Discussion on the intellectual property of automated content.
To minimize risks, it is key to stay informed about regulatory changes, especially in sectors with strict regulations such as healthcare and finance.
Quality and security of data
The effectiveness of AI depends directly on the quality of the information used. Some key considerations include:
- Incomplete or incorrect data → They may generate erroneous or unreliable answers.
- Biases in the models → If the training data are biased, the results may reflect this.
- Security risks → Protection of sensitive information against leaks or misuse.
- Dependence on external data → Some solutions require business-specific information to be truly effective.
According to Deloitte, 55% of companies avoid generative AI because of privacy and security concerns, underscoring the need for clear policies on these issues.
Lack of specialized talent
The shortage of trained professionals is a major obstacle to AI adoption. Among the most common challenges are:
- Deficit of specialists → 53% of Argentine companies report difficulties in finding talent in this field.
- Learning curve → Time is required to master new tools.
- Internal resistance → Not all teams adopt technology with the same readiness.
- Competition with large companies → Attracting and retaining technical talent can be complicated for SMEs.
To mitigate this problem, many companies resort to in-house training, partnerships with universities or hiring external experts, such as the services offered by KOLT in digital optimization.
Impact on employment and task reorganization
Automation brings with it changes in work dynamics. For an effective transition, it is important to consider:
- Evolution of roles → Redefine functions to take advantage of technology without displacing human talent.
- New opportunities → Creation of positions focused on AI supervision and optimization.
- Training and adaptation → Upgrading skills to integrate AI into day-to-day operations.
- Balance between automation and human control → Determine which tasks to delegate to AI and which to keep under direct supervision.
Companies that involve their teams in this process achieve a smoother transition and reduce resistance to change.
Measuring impact and return on investment
Quantifying the benefits of generative AI is not always straightforward. Some challenges include:
- Intangible results → Improvements in customer experience or service quality can be difficult to measure.
- Time horizons → Some benefits are not immediately reflected.
- Additional costs → Training, integration and maintenance expenses may not be contemplated from the beginning.
- Impact attribution → Determining which improvements are directly due to AI can be complex.
For an accurate assessment, it is advisable to combine quantitative metrics (cost reduction, sales growth) with qualitative indicators (customer satisfaction, operational efficiency), allowing a comprehensive view of the return on investment.
Insights and trends in generative AI for enterprises
The development of this technology is advancing at great speed, with innovations that will soon transform its use in companies. Some of the most relevant trends include:
- Multimodal models → Ability to simultaneously process text, images, audio and video.
- Advanced customization → Adaptation to specific sectors to offer more precise solutions.
- Reduced data dependence → More efficient models that require less information to generate quality results.
- Greater transparency → Tools that better explain how content is generated, facilitating its control.
- Integration with other technologies → Connection with IoT, blockchain and augmented reality for more complete solutions.
These advances will make generative AI even more accessible and effective for SMEs in the coming years.
New opportunities for companies
Progress in generative AI not only optimizes processes, but also opens doors to innovative business models. Some key opportunities include:
- Hyperpersonalization → Creation of experiences tailored to each customer in real time.
- AI-based services → Development of innovative products and solutions driven by artificial intelligence.
- Global expansion → Tools that facilitate adaptation to different markets and audiences.
- Increased collaboration → Systems that enhance creativity and productivity within work teams.
- Access to previously exclusive specialties → Democratization of knowledge and advanced tools.
SMEs that are able to identify and take advantage of these trends will be able to strengthen their position in the market and compete with larger companies.
Preparing for the digital future
To maximize the long-term potential of generative AI, it is critical to adopt a strategic approach that includes:
- Continuous learning → Encourage adaptability and constant updating within the company.
- Robust digital infrastructure → To have systems and processes that allow for the integration of new technological solutions.
- Strategic collaborations → Establish alliances with suppliers, academic institutions and other companies.
- Participation in innovation ecosystems → Connect with communities that promote the exchange of knowledge and experiences.
- Follow-up of technological advances → Keep updated on new applications and trends in AI.
The Artificial intelligence revolution in SMEs will continue to accelerate, and those that prepare in advance will be better positioned to take advantage of the opportunities of the future.
Conclusions and next steps
Key points for successful implementation
Generative AI offers Argentine SMEs the possibility to improve their efficiency, innovate and compete on equal terms with larger companies. To take advantage of its potential, it is essential to consider:
- Strategic focus → Define objectives aligned with the real needs of the business.
- Continuous training → Develop internal skills to optimize the use of technology.
- Responsible management → Incorporate ethical and safety principles from the outset.
- Impact measurement → Establish clear metrics to evaluate results and adjust strategy.
- Flexibility and adaptation → Remain open to new trends and evolve with technology.
Companies that integrate these elements in a structured way will be better prepared to capitalize on the opportunities offered by generative AI.
How KOLT can help your company
At KOLT We accompany SMEs in the adoption of advanced digital solutions, including generative AI, with a practical approach tailored to local market needs. Our work encompasses:
- Initial diagnosis → Identification of specific opportunities for your business.
- Customized strategy → Design of an implementation plan adapted to your resources and objectives.
- Tool selection → Advice on the choice of the most appropriate platforms.
- Specialized training → Team training to maximize the value of the technology.
- Assisted implementation → Accompaniment at each stage of the adoption process.
- Measurement and optimization → Impact assessment and strategic adjustments to improve results.
If your company is looking to integrate Generative AI in an effective and responsible way, we can help.
Request an interview with our specialists and find out how to make the most of this technology.