How large organisations are putting generative AI to work on their own data, from the team building AsscherAi. 48 articles.
Implementing AsscherAi requires choosing between an agent-based system and a fixed workflow, each committing you to different levels of investment in natural language processing, machine...
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Getting started with enterprise AI governance involves choosing a first case with a known answer, such as a shift supervisor checking the maintenance log, to verify results and build trust...
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Access control for AI enforces permissions at the point of retrieval, controlling what data the AI can access, as seen when a category manager uses AsscherAi to compare supplier data, and...
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Getting started with AI cost optimisation involves choosing a simple problem with a clear answer, like a shift supervisor checking the maintenance log to identify frequent repairs, then...
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Agentic AI streamlines supply chain management by planning and executing multi-step actions, such as querying the purchase order table to determine shipment due dates, and sending requests...
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Getting started with enterprise AI adoption requires attaching new capability to existing routines, such as using AsscherAi to analyse maintenance logs, allowing teams to verify AI-powered...
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Implementing AsscherAi for productivity involves choosing a first case with a known answer, such as the maintenance log, to test and refine the query process, then expanding to more complex...
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Getting started with AI process automation involves choosing a simple process with a known answer, mapping the current process, and identifying handoffs that create delays, a category...
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Enterprise AI security depends on where data is processed and stored, a purchasing manager must clarify this when procuring AsscherAi, considering factors like cloud provider compliance...
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Effective AI ROI measurement involves tracking leading indicators like user adoption and data quality, rather than relying solely on lagging indicators such as revenue growth, to accurately...
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Integrating AI systems with existing systems of record requires careful consideration of read and write paths, reconciling definitions, and handling latency and downtime, as a purchasing...
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Enterprise AI governance ensures the category manager and shift supervisor access relevant data, while enforcing permissions and auditability, to maintain trust and compliance, by...
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AsscherAi requires a deep understanding of the enterprise's data foundations, including field-level meaning and column names, to provide accurate answers, as a purchasing manager asking...
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AI cost optimisation reduces spend by analysing entire workflows, not just unit costs, and attributing spend to specific business processes, allowing organisations to make informed...
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Agentic AI workflows automate complex processes by integrating multiple systems, such as ERP and CRM, to complete tasks, like generating work orders and assigning technicians, making them...
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Enterprise AI adoption fails when systems are not integrated into existing workflows, making it easy to forget or ignore, but by attaching new capability to routines and providing...
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Generative AI supports executive decisions by assembling a consolidated view across functions on demand. Rather than commissioning a pack and waiting a week, a leader can ask a...
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Generative AI helps finance teams by shortening the path from a variance to its explanation. Instead of a multi-day drill through ledgers and commitments, a controller can ask what drove a...
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Generative AI helps R&D catch design failures earlier by making prior test results, review comments and project history searchable in context. Teams can ask whether a failure mode has been...
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Generative AI turns an HR policy library into something employees can query directly, answering in plain language and citing the document it came from. The gain is twofold: people get...
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Generative AI helps operations teams catch anomalies early by making a deviation cheap to investigate. Rather than waiting for a threshold alert or a monthly variance report, a team can ask...
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Generative AI improves sales forecasting less by producing a better number than by making the number inspectable. A sales team can ask which products drove a shift, how the pattern compares...
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Generative AI reduces unplanned downtime by making the signals that precede a stoppage easy to ask about. Instead of waiting for a weekly report, a production team can ask what deviated...
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Generative AI turns enterprise data into real-time answers by mapping a plain-language question onto the systems that hold the data, retrieving the relevant records, and composing a...
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