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Navigating the World of AI: Unlocking the Power of Data

Andy Birch, vice president, portfolio marketing for MRI Software

During a recent panel discussion – Make Smarter Decisions with AI-Powered Business Intelligence – I had the opportunity to unpack some key themes around the challenges and opportunities that Artificial Intelligence (AI) and Business Intelligence (BI) present for organisations navigating this era of innovation.

The Key to Unlocking AI’s Full Potential

A spotlight was shone on one key problem – data silos. It was identified that organisations often struggle to integrate data from multiple, unconnected systems, which limits their ability to build a ‘single source of truth’.

Andy Birch

For organisations operating within large structures – where communication across teams and systems can sometimes come across as fragmented – this issue becomes even more prominent and emphasises the need for organisations to map out and document all data sources to build a unified enterprise data strategy.

To fully leverage the paramount potential of AI, the priority must be on dismantling data silos. Creating a unified data environment is no longer a luxury, but a necessity. Through eliminating silos, organisations can enhance data integrity, ensure consistency, and enable real-time insights that improve decision-making.

Governance and Ethics

The importance of data governance and ethics is growing especially within smart cities and under government initiatives. The ethical complexities surrounding data usage in these environments were reinforced, and it was highlighted that without proper governance frameworks, data collection efforts could be at risk of being compromised with inaccuracies and biases.

For example, within smart city initiatives, understanding the business and general context behind data is key to building equitable solutions. The impact of poor data and governance etiquette can lead to flawed assumptions, which can then affect decision-making processes that impact entire communities. This isn’t just isolated to public sector projects but can also extend to the wider real estate world, where data-driven decisions influence planning and infrastructure development.

For businesses to really benefit from AI and BI, ethics and governance must be incorporated into their data strategy from the beginning. Public and private sector firms need to understand the importance of robust data governance to ensure accurate, fair, and ethical use of data overall.

Bridging the Gap Between Asset Management and Customer Experience

Operational challenges was another key focal point of the session and what many businesses face due to a lack of integration between asset management and customer centric systems. While many businesses resort to temporary fixes, these solutions are not sustainable and can lead to increased errors and efficiencies over time.

In the real estate sector, the consequences of poor data management can be critical. For example, inconsistent terminology or insufficient data standards can lead to a breakdown in communication not just within the organisation but also with external stakeholders, which can lead to below average decision-making and wasted resources.

There is a need for industry-wide data standards, such as OSCRE (Open Standards Consortium of Real Estate), to drive more efficient communication and operational efficiencies. OSCRE is a corporate member organisation which focuses on the development and implementation of real estate data standards. An interesting revelation pointed out the real estate sector’s slow adoption of these standards in contrast to the banking industry which has seen much faster progress.

For businesses to remain competitive, organisations must embrace data standards that streamline processes, enhance communication, and improve operational efficiencies. Investing now in consistent data standard practices can help in minimising the operational risks associated with fragmented systems and terminology

The Future of AI and Data – How to Balance Technology with Human Instinct

Without a doubt, AI will be key in revolutionising data-driven decision-making however, data-driven insights must be moderated by human oversight. AI can process vast amounts of data at lightning speeds but without any contextual understanding of the ethical implications, even the most sophisticated algorithms can lead to flawed conclusions.

This can easily occur in fields where community needs are to be assessed, and the poor level of data quality can produce biased outcomes that fail to accurately reflect the needs of underrepresented populations. Organisations need to prioritise data quality management, not only to ensure accuracy but also to remain accountable.

AI will become more ingrained in decision-making processes and now is the time where businesses need to invest in continuous data quality improvement. Human intuition and judgement will remain critical components of the decision-making process, especially where data directly impacts communities and customers.

Final Thoughts

The true success of any data strategy lies on its ability to enhance the customer experience. Businesses should not lose sight of the human element, particularly as AI-driven tools become more sophisticated. Poor data management can lead to wasted investments and missed opportunities to effectively serve customer needs.

The future of AI and BI lies in the careful integration of advanced technology with human values; AI should serve as a tool to elevate and enhance – not replace human decision-making.

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