Driving Business Outcomes with BOAT: Insights from Xebia & Appian’s Warsaw Event

From AI Hype to Business Outcomes: Focusing on What Matters 

A resounding theme of the forum was the need to pivot from AI hype to value-first implementation. The speakers emphasized that successful transformations start with clear business outcomes, not simply adopting AI for its own sake In practice, this means defining the metrics that matter – customer satisfaction, faster time-to-market, cost efficiencies – and using AI as a means to those ends. As one insight highlighted, even the most advanced AI initiatives must be justified by measurable impact on the business, rather than the novelty of the technology itself. This message resonated with the diverse audience: whether a CFO looking at ROI or an IT architect planning an AI rollout, keeping the focus on outcomes over features ensures that automation efforts deliver real value. In short, technology for technology’s sake took a backseat to AI with purpose – a crucial perspective for any enterprise seeking sustainable innovation. 

BOAT: Orchestrating Transformation with Intelligent Automation 

Business Orchestration and Automation Technology (BOAT) emerged as the cornerstone concept for achieving those outcomes. Recently recognized by Gartner as a new technology category, BOAT refers to unified automation platforms that consolidate disparate tools and processes into one cohesive system. Rather than stitching together isolated RPA bots, AI point solutions, and custom apps – which often leads to fragmented data and bloated IT costs – a BOAT platform provides a single orchestration layer for end-to-end processes. This consolidation not only cuts down on maintenance and licensing overhead but also gives organizations greater agility to adapt as business needs change. 

At the event, experts explained how BOAT integrates AI for smarter, dynamic business processes. In practical terms, this means AI isn’t a separate add-on; it’s woven into workflows to enhance decision-making and automation. For example, AI-driven rules can prioritize tasks or flag anomalies, while AI agents (autonomous assistive applications) handle routine inquiries – all within the same unified process. Appian’s low-code platform, as a prime example of BOAT, was highlighted as “the orchestration layer” that sits above fragmented systems, data sources, people, and bots. By orchestrating processes across people, systems, AI, business rules, and data, such a platform ensures automated workflows deliver their intended value and remain adaptable to changing conditions. As Appian is often described, it is “a software company that orchestrates business processes”, empowering organizations to design, automate, and optimize workflows from start to finish. In essence, BOAT platforms like Appian serve as the nerve center of intelligent enterprises – connecting legacy systems and modern AI into a harmonious whole. 

Why is this orchestration so critical now? As the forum discussions noted, the rapid adoption of cloud apps, AI services, and IoT has created a sprawl of siloed data and disjointed workflows in many organizations. BOAT addresses this by providing an agile glue – it seamlessly integrates systems and coordinates work across departmental and technological boundaries. This leads to real-time visibility for executives and managers, who can finally see the “big picture” of processes that span multiple teams and tools. The outcome is not just efficiency, but better business decisions: with unified data and processes, companies can react faster to market changes, ensure compliance in every step, and unlock new growth opportunities that were previously buried in organizational silos. As one event highlight succinctly put it, BOAT combines AI and automation to fuel smarter operations and dynamic processes – ultimately driving the business forward. 

AI in Action: Live Demonstrations Across Industries 

One of the evening’s high points was a series of live demonstrations, which made the theoretical concepts tangible. These demos showcased how an orchestrated approach to intelligent automation can be applied in real-world scenarios across banking, life sciences, and beyond. Attendees saw AI agents in action – running on the Appian platform – and how they seamlessly integrate with enterprise systems to solve complex, domain-specific challenges. Below, we recap two standout demos from the banking and pharmaceutical sectors that illustrated the power of AI-driven orchestration: 

• Banking – AI-Powered Client Lifecycle Management: In the banking demo, the audience followed the journey of a client onboarding process transformed by AI. Traditionally, bringing a new client on board (or updating an existing client’s profile) involves piles of forms, identity documents, compliance checks (KYC/AML), and coordination between front-office and back-office teams. Xebia’s demo showed how an AI-powered Client Lifecycle Management (CLM) solution can radically streamline this journey. For instance, when a prospective client submits documents, the system automatically classifies and extracts information from them (identifying passports, incorporation certificates, proof of address, etc.), eliminating tedious data entry. An AI agent embedded in the workflow can cross-verify the data against external databases and even summarize risk-related news about the client, supporting a risk-based KYC approach. Routine email inquiries or requests during onboarding are auto categorized and answered by the AI, so relationship managers spend less time on back-and-forth communications.
  
  All these steps are orchestrated in Appian: the platform presents a single unified client view to the bank’s staff, where data from multiple systems (CRM, core banking, compliance databases) is harmonized in one screen. The result is not only a faster process but a more consistent and transparent one – every task, from digital identity verification to account setup, flows through a central process with audit trails. The business impact of this AI-assisted CLM is significant: banks can see massive operational savings in both cost and time, and faster client onboarding directly translates to faster revenue realization. In fact, similar solutions have reduced onboarding times by up to 50% in practice. The demo underlined how enhancing compliance and customer experience need not be trade-offs – with intelligent automation, banks achieved both a streamlined, paperless onboarding (fewer manual steps for the customer, higher satisfaction and stronger compliance checks (since AI never forgets a required step). It was a compelling illustration of making a traditionally cumbersome process into a competitive advantage using BOAT principles. 
  
  
• Pharmaceuticals – AI-First Process Automation with Compliance: The forum also featured a deep dive into the life sciences domain, showing how an “AI-first” approach can accelerate pharma operations while maintaining strict compliance. In highly regulated industries like pharma, processes are often split into “clinical” (related to drug trials, patient data, etc.) and “non-clinical” (manufacturing, regulatory filings, quality control) – both sides rife with documentation and compliance checkpoints. The live demo walked through a scenario of automating a clinical trial support process with generative AI. For example, an AI agent could assist in adverse event reporting during a trial: it can ingest free-text reports from investigators, classify the severity, and draft summary reports for pharmacovigilance officers to review. Similarly, on the non-clinical front, the demo showed an automation of a regulatory submission process – an AI could pull required data from various systems to fill out compliance forms and even generate a first draft of a submission dossier or a validation report.
  
  All of this was orchestrated on the Appian platform, which means every AI action (every data retrieval or document generation) was tracked and auditable. This point is crucial for pharma compliance (GxP): the system provides auditable records and versioning for each step, ensuring that the use of AI does not compromise traceability or integrity. Thanks to the low-code nature of the platform, if a new regulation comes out or a process needs change, the workflow can be rapidly adapted – a far cry from the hard-coded processes of the past. The demonstration made it clear that “AI-first” doesn’t mean no humans in the loop; rather, it means AI does the heavy lifting of parsing data and making routine decisions, so human experts can focus on oversight and exceptions. The outcome is faster cycle times – imagine cutting down a clinical data analysis from weeks to days – and a significant reduction in manual errors (which, in compliance, are costly). In short, the pharma use-case reinforced that intelligent automation is as much about ensuring quality and compliance as it is about speed. By rethinking processes with AI at the center, pharmaceutical companies can drive innovation (faster research, more efficient trials) without falling afoul of regulators. As the forum noted, this creates “new paradigms for compliance and innovation” in an industry historically slow to change. 
  
  
• Beyond Banking and Pharma – Broad Enterprise Impact: While banking and life sciences provided concrete examples, the strategies discussed have broad relevance across industries. Whether it’s insurance claims processing (another area where AI-driven orchestration is delivering big wins in efficiency and accuracy) or supply chain management, the core idea is the same: unify your data and workflows on a single platform, inject AI where it adds insight or speed, and keep humans in control of outcomes. Attendees noted that in insurance, for example, an integrated platform can connect customer incident data with policy systems and AI fraud detectors to settle claims faster. In retail and manufacturing, opportunities abound to use AI agents for everything from demand forecasting to automated compliance checks on production lines. By showcasing multiple domains, the event drove home that BOAT and intelligent automation are industry-agnostic – any process that spans people, systems, and data can likely be improved with this approach. The live demos served as a springboard for attendees to imagine similar transformations in their own organizations, and the energy in the room suggested many were already seeing new possibilities. 

Xebia’s AI Value-Assessment Framework: Navigating the Journey 

To help organizations chart their path forward after inspiration from these use cases, Xebia introduced its AI Value-Assessment Framework. This framework is essentially a structured methodology for evaluating an enterprise’s AI maturity and ROI potential. Many leaders struggle with questions like: Where do we stand today in terms of AI readiness? What use cases should we prioritize? How do we balance quick wins versus long-term innovation? The AI Value-Assessment Framework addresses these by examining multiple dimensions of the business and technology. It looks at classic AI maturity factors – such as the quality of data assets, availability of skilled talent, and existing analytical capabilities – as well as the business adoption and value side – such as executive support, culture, and clearly defined outcome metrics. By scoring or mapping an organization across these dimensions, the framework provides a holistic view of where the company is on its AI journey. 

Crucially, this isn’t just an IT assessment. The framework ties each aspect of AI maturity to potential business benefits, essentially asking “If we improve this area, what value (qualitative and quantitative) could it unlock?” In doing so, it ensures that any next steps in AI adoption are grounded in business value. As industry advisors often note, an effective AI assessment considers both the hard numbers and the softer benefits– for example, not just the potential revenue increase from an AI use case, but also improvements in customer experience or decision-making quality that it brings. Xebia’s approach captures this balance. It was evident that this framework resonated with the executive audience: by translating the nebulous concept of “AI readiness” into a pragmatic roadmap, it becomes much easier to secure buy-in and plan investments. One could imagine a CIO or Chief Digital Officer leaving the event thinking, “Let’s first find out our AI maturity level and top gaps, and then address those systematically.” Indeed, Xebia mentioned their AI Maturity Scan offering, which quickly benchmarks a company on these scales and identifies priority areas for improvement (e.g. maybe data governance is a bottleneck, or perhaps the organization needs more training for business leaders on AI possibilities). The underlying message was empowering: no matter where a company currently stands – whether just experimenting with RPA or already deploying neural networks – there is a clear path to elevate to the next level, guided by a focus on value. As one Xebia expert put it, adding a dozen data scientists to your team won’t magically make you AI-driven if the business side isn’t prepared to change; true success comes from growing analytical capability and business adoption in tandem. The AI Value-Assessment Framework helps pinpoint those needs and align stakeholders around a common vision of “AI for business outcome”, echoing the event’s central theme. 

Key Takeaways for Enterprise Leaders 

Throughout the event, a few key insights surfaced repeatedly – insights that both technical teams and executive leaders could take home to their organizations: 

1. Business Outcomes First, Technology Second: Whether evaluating a new AI tool or an automation project, start by defining the business outcome you seek. Increase in customer retention? Reduction in processing time? Compliance error elimination? Being outcome-driven keeps projects on course to deliver tangible results. This mindset also helps in communicating the “why” to stakeholders beyond IT. 
2. Unified Platforms Beat Point Solutions: The case for BOAT was made loud and clear – having a unified platform for automation and orchestration (like Appian) avoids the trap of siloed, piecemeal solutions. Enterprises with unified automation see lower IT overhead and faster change management. In an era where speed and adaptability are competitive advantages, this is a critical consideration for CIOs planning their architecture. 
3. AI is an Enabler, Not the End Goal: The AI agents and features showcased were impressive, but they were always presented in the context of a larger business process. This reinforced the idea that AI by itself isn’t the hero of the story – the business process and the people are. AI plays a supporting role, albeit a powerful one, to augment human decision-making, handle grunt work, and provide insights at scale. Keeping AI “grounded” in this way helps maintain trust and clarity on its purpose. 
4. Measure, Monitor, and Iterate: Several presenters noted the importance of metrics and monitoring. For example, if you deploy an AI agent for customer service, track how it improves resolution times or customer satisfaction. The IntelliAgent solution that won Xebia an Appian Innovation Award features real-time AI usage monitoring and enterprise-wide sharing of successful agents – underscoring how measurement and cross-pollination of AI solutions can accelerate value delivery. Enterprise decision-makers appreciated that adopting AI/automation is not a one-and-done project but an ongoing journey of improvement. 
5. Compliance and Governance are Non-Negotiable: Particularly for industries like finance and pharma, any AI/automation initiative must bake in compliance from day one. The event demonstrations showed that with the right platform, maintaining an audit trail and enforcing rules can be automated just like any other step. Leaders were urged to involve risk and compliance teams early in the design of AI-driven processes – turning potential skeptics into partners by design. This not only avoids headaches later but can actually enhance compliance (for instance, by automatically validating that every required approval or check has happened in a process). 

Ultimately, the consensus was that intelligent automation is reaching a maturity where organizations can trust it for mission-critical operations – provided they approach it with a clear strategy and strong governance. The technology (AI, low-code, etc.) has leapt forward in recent years; now the differentiator is how you apply it in your unique business context. 

Conclusion: Orchestrate Your Transformation – and Let’s Talk 

The Business Orchestration and Automation Technology (BOAT) event in Warsaw delivered a powerful message: to thrive in the AI era, enterprises must harmonize technology with purpose. It’s about orchestrating people, data, and systems with AI in a way that fundamentally improves your business. From the enthusiastic discussions and Q&A, it was clear that organizations are ready to move past experimentation and take bold, outcome-driven actions. But you don’t have to embark on this journey alone. 

Now is the time to turn these insights into action. Whether you’re just starting to explore intelligent automation or looking to scale up your AI initiatives, Xebia’s team stands ready to collaborate. We encourage you to initiate a conversation with us – share your challenges and ambitions, and let’s explore how to orchestrate a solution together. This could mean scheduling a tailored workshop to identify high-impact use cases, engaging in an AI Value Assessment session to roadmap your next 6–12 months, or even a live demo customized to your industry. The goal is to connect the dots between today’s discussion and tomorrow’s execution. 

Inspired by what you heard? Let’s keep the momentum going. Our experts can dive deeper into the strategies and technologies that piqued your interest and help craft a plan that fits your organization. As underscored during the event, the journey to intelligent, outcome-driven operations is a collaborative one. Reach out to Xebia to explore how we can partner in accelerating your transformation – whether it’s through adopting Appian as your orchestration platform, injecting AI agents into your workflows, or simply brainstorming the art of the possible. The dinner in Warsaw may have concluded, but the real transformation feast is just beginning.

Now’s the moment to get in touch, and let’s orchestrate the future of your business together.