Artificial intelligence is everywhere – in headlines, business plans, and on everyone’s lips. But behind the hype lies a fundamental question: how do you turn the promise of AI into real, measurable results? This question was answered by the AI experts and enthusiasts from our BlueRider.Software team, Julia Dudowicz and Agnieszka Ruczaj, who returned from the Women in Tech Summit 2025 with concrete observations and inspirations.
That’s why they shared with us how tech giants – Salesforce, Hitachi, and Pega – are moving beyond buzzwords to implement solid strategies and tools that are truly changing the game. Fasten your seatbelts, because we’re taking you behind the scenes of real AI implementations.
Salesforce: AI is a Complete Ecosystem, Not Just a Language Model
Key takeaways were clear from Salesforce’s presentation: effective AI implementation is about more than just a large language model (LLM). Salesforce approaches the topic holistically. Their Agentforce concept is based on the collaboration between people and AI agents. This approach is crucial because a true digital transformation requires a coherent ecosystem that combines agents, applications, and data.
This strategy is built on four pillars:
- A precisely defined business goal.
- An audit and understanding of existing processes.
- The creation of scalable, reusable patterns.
- A focus on measurable business impact.
In practice, Salesforce looks for repetitive, high-volume tasks (so-called “good use cases”) and then automates them in departments like HR, sales, or IT.
Pega: The No - Code Democratization of AI
Pega, on the other hand, presented a completely different approach during its presentation, centered on the motto “No code, no problem.” Their goal is to make the power of AI accessible to non-technical users. The GenAI-powered Blueprint tool, which can generate complete process diagrams in seconds, is the best example of this.
This approach raises an interesting question about the differences in business benefits.
Feature Breakdown: Agentforce vs. Blueprint
Aspect
Salesforce Agentforce (AI Agents)
Pega GenAI Blueprint (No-code)
Goal/Model
This is an advanced “digital labor” platform based on AI agents that operate autonomously or in collaboration with people. It focuses on automating tasks in areas such as customer service, sales, and marketing.
This is a no-code/low-code tool that supports application and workflow design. Generative AI creates a ready-made process template, allowing the user to quickly design a solution without coding, based on best practices.
Key Features
It enables the creation of specialized agents, CRM integration, central oversight (Command Center), and ensures security through built-in AI guardrails.
It offers a workflow creator with industry templates, a menu of ready-to-use tasks for automation, process visualization, and UI generation by AI.
Business Benefits
It accelerates customer service and internal processes, increases employee productivity, and lowers service costs through extensive automation.
It guarantees faster application deployment (shorter time-to-market), reduces time-consuming analytical work, and allows for better use of industry knowledge and patterns.
Human Role
Decisions and oversight remain in the hands of users. AI assists and performs routine tasks, but experts define goals and improve processes.
AI generates an initial draft, but the final shape of the process is a result of collaboration between business and IT. The user accepts and modifies the generated solution.
Statistics
Since October 2024, the platform has increased customer retention by 22% and autonomously handles 70% of inquiries. It has been implemented in 8,000 companies in 6 months.
In less than 3 months since its premiere, users have built 35,000 free applications. Forrester described the tool as delivering “the first, optimal process draft, built on the basis of expert knowledge.
Salesforce vs. Pega – Where Do the Key Differences Lie?
We asked our expert, Julia Dudowicz, to explain. Here’s her breakdown:
- Salesforce Agentforce: Uses AI agents to automate and perform tasks (a “digital workforce”). The main benefit is increased productivity and lower operational costs.
- Pega GenAI Blueprint: Uses AI to design and generate application templates in a no-code model. The main benefit is a radical acceleration of the software development process.
Simply put: Salesforce automates work, while Pega automates the creation of tools for work. As a result, we see that AI can support not only operations but also the process of creating technology itself. This is precisely the approach we implement with our clients—always with a specific business outcome in mind.
Hitachi: Prompt Engineering, the Art of Precise Communication with AI
Even the best AI engine is useless if we don’t know how to command it. That’s why, as our AI enthusiast Agnieszka Ruczaj emphasized, Hitachi places a huge emphasis on prompt engineering. So, how do you create a command that an AI will understand flawlessly?
The 6 Key Elements of an Effective Prompt
According to Hitachi’s experts, an effective prompt must contain 6 elements:
- Role
- Context
- Specificity
- Tone
- Format
- Examples
What’s more, the Chain of Thought (CoT) technique—asking the AI to explain its reasoning process – dramatically increases the precision of the results.
The Most Common Mistake in Prompt Engineering and How to Avoid It
It sounds simple, but in practice, it’s easy to make mistakes. We asked Agnieszka out of curiosity what the most common pitfall for beginners is. Here’s what she explained:
The most common and, at the same time, easiest mistake to avoid is giving imprecise or overly general instructions.
- Bad Example: Write a text about cats.
- Good Example: Write a short, funny blog post (approx. 200 words) for animal lovers, describing 3 funny facts about domestic cats. Use a lighthearted tone and end with a question for the reader.
The Common Denominator of Success: What Connects the Giants' Strategies?
So, what connects the strategies of these giants? Analyzing their approaches reveals several common threads that define mature AI implementations:
- Strategy Before Technology: First the goal, then the tools.
- Systems Thinking: Instead of isolated applications, creating integrated ecosystems.
- Focus on Practicality: Automating specific and scalable tasks.
- Tools for People: Intuitive platforms for domain experts, not just engineers.
How to Measure the ROI of AI Implementation?
The first point – strategy and goals – is crucial. But how do you measure that success? This is one of the biggest challenges. Julia Dudowicz explains the problem.
What is the biggest challenge in measuring the return on investment (ROI) for AI? Above all, it’s the intangible nature of its effects. Many benefits are difficult to measure precisely and attribute to specific AI actions.
The main problems are:
- Difficulty in Isolating AI’s Contribution: AI usually supports multiple departments at once, making it hard to assess its standalone impact.
- Insufficiency of Classic ROI: This is because traditional financial metrics often fail to capture the full value AI brings. This value includes aspects like increased productivity, improved customer service quality, or higher employee satisfaction.
That’s why experts suggest expanding metrics to include qualitative and indirect indicators. It’s worth considering, for example, Return on Employee Investment (ROIE), Time to Value, or user technology adoption metrics.
Conclusion: From Fascination to Practice
The conclusions from the Women in Tech Summit 2025 are clear: the era of fascination with AI has long given way to the era of its practical application. Artificial intelligence is becoming a standard, measurable, and powerful tool for solving real business problems. The question is no longer “if” but “how” to implement AI.
Practical AI Tips for Smaller Companies
But what about companies that aren’t tech giants? We asked Agnieszka Ruczaj for advice.
- Automate Repetitive Tasks: Use ready-made AI-as-a-Service tools (e.g., ChatGPT, Zapier with AI, Notion AI, Grammarly, Tidio) to automate customer service, content writing, or preparing offers. You can generate e-commerce product descriptions, create automated chat responses (chatbots), or draft emails.
- Foster a Culture of Learning and Experimentation: Organize internal AI hackathons, training sessions, or pilot implementations. Give people a chance to experiment. A good idea is to periodically test new AI tools (e.g., HeyGen, Runway, Claude) or create a shared company list of “AI tips” for daily work.
Need
AI Tool
Cost
Content creation
ChatGPT Plus, Notion AI
~$20/month
Customer service
Tidio, ChatGPT with context
~$30/month
Automations
Zapier with AI, Make.com
Free/low
Visualizations/reports
Excel + Copilot / GPT + Sheets
Low
Custom website chatbot
Chatbase, Botpress, Flowise
Free/low
Important Links
For all who wish to delve deeper, we’ve gathered the official sites and resources for the discussed technologies below:
Women in Tech Summit – Official site of the global summit.
Salesforce Einstein 1 Platform – The product page for Salesforce’s AI.
Hitachi’s AI Solutions – The official overview of Hitachi’s AI solutions.
Pega GenAI™ – The page dedicated to generative AI in the Pega platform.
Our participation in the Women in Tech 2025 only confirmed what we see daily in our work with clients: AI genuinely improves processes in companies across various industries. Thanks to valuable conversations and inspirations, we’ve brought back even more ideas on how to wisely use artificial intelligence in practice.
Day to day, we help companies automate repetitive tasks, optimize work time, and create solutions that have a real impact on business growth.
Want to see how AI can work in your company? Let’s talk. We’ll show you concrete applications and help you match the technology to your needs. Let’s talk about how these ideas can help your business spread its wings.