Cutting Through the AI Hype: How Businesses Can Turn Innovation into Real Outcomes

Caique Zaniolo
VP Product
As I started my new role as VP of Products at Cyferd, I focused my attention on the challenges businesses face. The landscape is increasingly complex and competitive. It demands companies be more agile, data-driven, and innovative while managing costs. To aggravate these concerns, the people managing these companies need to create plans and provide answers for how they will react to the buzzwords of digital transformation and AI, but the reality is far more intricate.
Many businesses are pouring resources into AI, automation, and data-driven decision-making, hoping to gain a competitive edge. But I’ve noticed that for many, the real challenge is not the technology itself. It’s making sure those investments actually pay off. Too often, AI projects are launched without a clear purpose for how they’ll deliver actionable insights or drive tangible business results. Resources get spread too thin, and leaders are left asking, “Are we really seeing the value we expected?”.
That’s where the real problem lies! In a scenario filled with shiny new tools, the focus must shift back to business outcomes. How can organizations adopt new technologies and ensure these tools optimize operations and drive growth? It’s one thing to have access to AI or automation, but it’s entirely different to track, measure, and adjust those efforts so they translate into real-world benefits.
Take data management, for instance. Every company knows data is critical, but it’s not just about having data; it’s about using it effectively. Many businesses struggle with siloed data, poor governance, and inconsistent quality. This makes it nearly impossible to gain reliable insights, let alone fuel effective AI strategies. AI efforts quickly lose direction without a centralized and governed data repository. Resources are wasted, and the business impact is minimal.
And then there’s the pressure to do more with less. In an economic climate where efficiency is everything, businesses are looking for ways to cut costs without sacrificing innovation. The problem is that scaling back often leads to operational bottlenecks or missed opportunities without the right tools and infrastructure. Leaders need solutions that don’t just automate for the sake of automation but actually optimize processes, drive efficiency, and scale without a hitch.
The solution to these challenges isn’t found in isolated tech fixes. Companies need a holistic approach to managing data, deploying AI, and streamlining processes. They need solutions that empower their teams to turn business goals into actionable outcomes. These solutions must be flexible enough to adapt to a constantly changing environment and be robust enough to provide stability and security.
At Cyferd, our goal is to confront these business problems head-on. We believe in enabling companies to optimize their AI efforts and providing a governed way to prevent external vendors from exploiting their data. My plan is to continue to evolve a clean roadmap focusing on removing data silos and ensuring our customers have access to a clean, actionable, governed, ready to use, and centralized data repository that provides quality and consistency. That is the foundation of any successful AI strategy. Front and center on this product roadmap is Neural Genesis, our proprietary AI capability, to unlock the potential for smart automation to pave a path of optimization and higher results. My experience and feedback from our customers and partners tell me it’s not just about providing businesses with the latest technology; it’s about ensuring that these technologies work together seamlessly to solve real business problems.
Suppose your company handles a process in a very particular way. In that case, it will never find an out-of-the-box solution to solve it. Your process may not be the best possible version, but it is applied today, and your company relies on it. You need a platform to accompany you on that journey. Cyferd’s approach is to meet you where you are and create the foundation for your evolution to flourish.
For businesses feeling the pressure to innovate while cutting costs, we provide the tools to make it happen without getting bogged down by complexity. By focusing on solutions that scale and evolve with their needs and ensuring every AI-driven insight is actionable, we help them make the best use of their resources—and ultimately, drive better business outcomes.
As I settle into my new role, I’m excited to dive deeper into these problems, engage with our customers, and continue to push for solutions that address their most pressing challenges. Businesses are constantly evolving, and we need to ensure they have the tools to not just survive but thrive in the face of uncertainty. I’m confident that Cyferd can deliver the necessary solutions to turn challenges into opportunities.
Find out more About Cyferd
New York
Americas Tower
1177 6th Avenue
5th Floor
New York
NY 10036
London
2nd Floor,
Berkeley Square House,
Berkeley Square,
London W1J 6BD
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Comparisons
BOAT Platform Comparison 2026
Timelines and pricing vary significantly based on scope, governance, and integration complexity.
What Is a BOAT Platform?
Business Orchestration and Automation Technology (BOAT) platforms coordinate end-to-end workflows across teams, systems, and decisions.
Unlike RPA, BPM, or point automation tools, BOAT platforms:
- Orchestrate cross-functional processes
- Integrate operational systems and data
- Embed AI-driven decision-making directly into workflows
BOAT platforms focus on how work flows across the enterprise, not just how individual tasks are automated.
Why Many Automation Initiatives Fail
Most automation programs fail due to architectural fragmentation, not poor tools.
Common challenges include:
- Siloed workflows optimised locally, not end-to-end
- Data spread across disconnected platforms
- AI added after processes are already fixed
- High coordination overhead between tools
BOAT platforms address this by aligning orchestration, automation, data, and AI within a single operational model, improving ROI and adaptability.
Enterprise BOAT Platform Comparison
Appian
Strengths
Well established in regulated industries, strong compliance, governance, and BPMN/DMN modeling. Mature partner ecosystem and support for low-code and professional development.
Considerations
9–18 month implementations, often supported by professional services. Adapting processes post-deployment can be slower in dynamic environments.
Best for
BPM-led organizations with formal governance and regulatory requirements.
Questions to ask Appian:
- How can we accelerate time to production while maintaining governance and compliance?
- What is the balance between professional services and internal capability building?
- How flexible is the platform when processes evolve unexpectedly?
Cyferd
Strengths
Built on a single, unified architecture combining workflow, automation, data, and AI. Reduces coordination overhead and enables true end-to-end orchestration. Embedded AI and automation support incremental modernization without locking decisions early. Transparent pricing and faster deployment cycles.
Considerations
Smaller ecosystem than legacy platforms; integration catalog continues to grow. Benefits from clear business ownership and process clarity.
Best for
Organizations reducing tool sprawl, modernizing incrementally, and maintaining flexibility as systems and processes evolve.
Questions to ask Cyferd:
- How does your integration catalog align with our existing systems and workflows?
- What is the typical timeline from engagement to production for an organization of our size and complexity?
- How do you support scaling adoption across multiple business units or geographies?
IBM Automation Suite
Strengths
Extensive automation and AI capabilities, strong hybrid and mainframe support, enterprise-grade security, deep architectural expertise.
Considerations
Multiple product components increase coordination effort. Planning phases can extend time to value; total cost includes licenses and services.
Best for
Global enterprises with complex hybrid infrastructure and deep IBM investments.
Questions to ask IBM:
- How do the Cloud Pak components work together for end-to-end orchestration?
- What is the recommended approach for phasing implementation to accelerate time to value?
- What internal skills or external support are needed to scale the platform?
Microsoft Power Platform
Strengths
Integrates deeply with Microsoft 365, Teams, Dynamics, and Azure. Supports citizen and professional developers, large connector ecosystem.
Considerations
Capabilities spread across tools, requiring strong governance. Consumption-based pricing can be hard to forecast; visibility consolidation may require additional tools.
Best for
Microsoft-centric organizations seeking self-service automation aligned with Azure.
Questions to ask Microsoft:
- How should Power Platform deployments be governed across multiple business units?
- What is the typical cost trajectory as usage scales enterprise-wide?
- How do you handle integration with legacy or third-party systems?
Pega
Strengths
Advanced decisioning, case management, multi-channel orchestration. Strong adoption in financial services and healthcare; AI frameworks for next-best-action.
Considerations
Requires certified practitioners, long-term investment, premium pricing, and ongoing specialist involvement.
Best for
Organizations where decisioning and complex case orchestration are strategic differentiators.
Questions to ask Pega:
- How do you balance decisioning depth with deployment speed?
- What internal capabilities are needed to maintain and scale the platform?
- How does licensing scale as adoption grows across business units?
ServiceNow
Strengths
Mature ITSM and ITOM foundation, strong audit and compliance capabilities. Expanding into HR, operations, and customer workflows.
Considerations
Configuration-first approach can limit rapid experimentation; licensing scales with usage; upgrades require structured testing. Often seen as IT-centric.
Best for
Enterprises prioritizing standardization, governance, and IT service management integration.
Questions to ask ServiceNow:
- How do you support rapid prototyping for business-led initiatives?
- What is the typical timeline from concept to production for cross-functional workflows?
- How do licensing costs evolve as platform adoption scales globally?
