Strategy & Transformation

ERP Failure and Lessons in Focus

In November 2023, IBRS published an article titled ‘The Top Reasons Why ERP Projects Fail – Lessons From the Front’, which explored the top seven reasons why ERP projects fail and how to mitigate them. In the short time since, we have seen the reporting of a number of high profile ERP projects that have been abandoned with costs in the 70–200 million dollar range.

It is timely to look back, so this article will advise on reinforcement and subsequent advice that can be offered today as a result.

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Enterprises Need AI Systems, Not Chatbots

To truly harness the transformative power of artificial intelligence (AI), enterprises must shift their focus from standalone AI applications to comprehensive AI systems that are deeply integrated into their existing workflows and processes.

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Large Language Models as an Integration Layer in Enterprise Applications

Embracing large language models as an integration layer can enable enterprise application development by providing a natural language interface between diverse systems, APIs, and human users. This approach allows seamless data flow, intuitive user experiences, and rapid prototyping of complex applications, dramatically reducing development time and costs while opening new avenues for innovation and process optimisation across the organisation.

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Mitigating AI Bias for Equitable AI in the Enterprise

Artificial intelligence (AI) bias threatens to undermine the fairness and effectiveness of enterprise AI solutions. We examine key types of AI bias, their real-world impacts, and practical mitigation strategies – focusing on examples from Australia, New Zealand, and India. Learn key approaches to develop more equitable AI systems that serve diverse populations and unlock the full potential of AI for your business.

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Measuring The Effectiveness Of Virtual Assistants

As large language model (LLM)-based virtual assistants continue to permeate various aspects of enterprise operations, measuring their effectiveness becomes crucial and more complex. The key lies in developing a holistic measurement framework that combines traditional metrics with novel approaches tailored to each specific use case.

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