From Desktop AI to Enterprise AI

With a new Enterprise AI Architecture, BlueCallom helps businesses transition from Desktop AI to Enterprise AI.

AI POWER FOR THE DESKTOP

Over the past two years, artificial intelligence has made clear how it can transform businesses by improving individual tasks and jobs such as writing reports, making forecasts, assessing legal documents, and creating business plans. Chatbots, co-pilots, prompts, and individual AI agents have become valuable productivity tools for millions of individual professionals.

At the same time, however, enterprise leaders expressed their disappointment that none of the promises, like accelerating the enterprise, increasing productivity by an order of magnitude, so that profitability could rise significantly, came true. Mission-critical business processes rarely involve a single user or a single AI agent. They span departments, applications, workflows, approval processes, data sources, and hundreds of interconnected business decisions. Desktop AI was never designed to operate at this scale.

EARLY ENTERPRISE AI

When we at BlueCallom built our first AI-based Enterprise Innovation System in January 2023, a month after ChatGPT was introduced, we did not think of individual engineers but of entire innovation teams. We did not focus on a single-step workflow for ideation; instead, we began with the much-needed multitude of interdisciplinary workflows.

Eight major innovation process elements were included: Innovation Opportunity Discovery, which introduced a new technique called Neuro-Ideation, followed by Innovation Validation. Once successful feedback was given to Innovation Financing, the development of the BluePrint for Innovation Production and, in parallel, the Go-To-Market strategy and Sales Model Development began. Then eventually scaling.

These eight major, non-linear steps are of very different natures, teams, and workflows. Yet, they are very interconnected. Little did we know this would be our starting point for Enterprise AI Workflows.

FIRST ENTERPRISE AI ARCHITECTURE & PLATFORM

A year later, in early 2024, we expanded our thinking, mindset, and technology to a foundational Enterprise AI platform. Not only for Innovation management but also for any other business application and workflows. But that required another new technology: the Enterprise AI Workflow, or Enterprise Workflow Intelligence, as we call it today.

THE TRANSITION FROM DESKTOP AI TO ENTERPRISE AI

• Desktop AI like Chatbots, Co-Pilots, and Agents will still exist and help individuals with individual tasks, but they are not mission-critical solutions. Also, the origin of those desktop AI tools is all too often unknown. Individual agents often come from different sources or are even homegrown by internal developers in a DIY (Do-It-Yourself) manner.
• This is all ok as long as those individual tools are not mission-critical. But once AI becomes mission-critical, the way we use and manage it changes. The noise on the street is still all about the models, benchmarks, data protection, and more. But those aspects are not a roadblock.

The roadblock was the lack of technology to put it all together into a holistic and homogeneous Enterprise AI Architecture.

Enterprises don’t buy models, GPUs, or benchmark data, they buy measurable, manageable and scalable business results.

• Enterprise AI is not a tool for individuals but a solution for large-scale organizations. It is a solution that can deliver a hard-to-believe 50%+ productivity gain once implemented homogeneously across all departments. At its core, it isn’t about individual tasks but adaptive and intelligent workflows that take over 50% of the workload and do it in a fraction of today’s time. It extends human intelligence, accelerates business workflows, and reduces employees’ overhead and administrative work. Today’s Enterprise AI solutions are proactive and no longer just respond to human inputs. The Workflow Intelligence reached a level of speed and precision that is faster and more precise than any human. Allowing teams to do twice as much with less stress.
• For that, it needs a very different architecture. It can’t be just a Question & Answer system; it has to be a workflow management system. It’s not just for a single user but for entire teams, even cross-functional collaboration. It must be aware of the organization it works in, its departments, country offices, and ideally include business partners and alliances. It needs to handle corporate data far beyond what conventional software ever could. It needs to manage countless intelligent artificial beings that work at light speed. Instead of Python-Code Agents and time- and money-consuming orchestrators, it needs Native AI.
• While we had to build our own Native AI development system, it became clear that the technological complexity of such a platform, the necessary applications, and the required workflow intelligence would soon cause do-it-yourself AI enthusiasts to give up building their own systems. Not because of complexity, but because of their know-how, but because of their inability to maintain and expand such a system at scale.
• Then there is the need for enterprise-wide analytics, management dashboards, employee rights and roles, and overall administration. Moreover, Enterprise AI needs an AI economics model that provides ROI visibility, distributed consumption accounting across departments, and Digital AI Asset Management across the enterprise.

Enterprise AI is a holistic, mission-critcal, enterprise-wide solution, that provides Workflow Intelligence, AI Economics, and corporate manageability at scale.

THE ENTERPRISE AI TODAY

Holistic, Interconnected Enterprise AI Solution
Enterprises can now transition to complete AI-powered business systems across Sales, Marketing, Logistics, Finance, Human Resources, Research & Development, Customer Service, and other business functions. The company’s data will be leveraged as long as the company wants. Data cleansing is not necessary, as the AI is intelligent enough to handle what we might call convoluted data. The existing IT operation can continue as is.

Agentic IT Technology
Because of the Native AI Architecture, those native AI agents are no longer hardcoded but dynamic, adaptive, intelligent units. Each Enterprise AI Application consists of intelligent workflow networks, multiple clusters of Native AI agents, enterprise data sources, existing business applications, and human experts working together as one adaptive system.

AI Network Design
Unlike conventional software projects that require replacing existing systems, AgenticBlue adds an intelligent orchestration layer atop current enterprise applications, protecting prior IT investments while enabling a new generation of AI-powered workflows.

User Adaption
Adaptation is simple. The user needs a browser and can start working immediately. There are no complex masks to feed data into a system or query data for reports. There is no “process” the use needs to worry about and avoid mistakes. Users are guided by the AI as part of the workflow intelligence.

Enterprise AI Economics
Built on BlueCallom’s Native AI Architecture, applications are developed almost entirely using AI. This dramatically reduces development time and cost and simplifies customization. Organizations can deploy production-grade Enterprise AI Applications within weeks rather than months while continuing to leverage their existing enterprise software landscape. The ‘Pay-for-Gain’ business model is designed so that the cost of the usage is always more profitable than the manual work. This allows for instant ROI, which can be reviewed in real time.

Enterprise AI Deployment
When transitioning to Enterprise AI, your existing systems will be leveraged but not changed. Even within the same department, you can have employees work on the AI side while others still work on the existing systems. There is no timeline for switching, and there is no need to switch at all.

Enterprise AI Analytics
Enterprise AI Analytics transforms enterprise data into executive understanding.

We span a virtual Enterprise AI Network across your entire organization, maintain connections to your existing systems and data (no cleansing needed), and provide your teams with data and results within the AI systems.

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To learn more about Enterprise AI, consider exploring our
Enterprise AI BrainCamp, an intense one-day training in Zürich or Online
Enterprise AI for Executives, an intense one-day workshop in Zürich