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Resource Management Maturity
The complete blueprint to transform your resource management.
Learn moreOriginally featured in AIT.
Interest in AI has risen sharply in 2023, but as with all advances in technology, it’s not exempt from the perceived risks of adoption. Whether that be mass market AI tools such as Chat GPT or accountancy specific AI systems, public resistance to AI remains. However, with great benefits to gain from using AI, learning how to navigate the risks and reap the rewards is increasingly important for firms.
Whilst AI’s promise is huge, people are still acutely cautious with three out of five people (61%) reporting either ambivalence or an unwillingness to trust AI systems. Even within firms that have significantly invested in AI, such as Deloitte, barriers to both starting and scaling AI projects remain.
So what’s holding firms back?
Findings from Trust in Artificial Intelligence: A global study published in 2023 by KPMG
According to the Deloitte report, 50% of respondents cited AI-related risks as a barrier to scaling AI projects. These AI-related risks mirror the ethical AI concerns often covered by the media. The risks include a lack of explainability and transparency in AI decisions, data privacy or consent management issues, and general safety concerns around AI systems. Whilst these are understandable concerns, not all are valid.
Given that understanding AI sets a foundation for trust, it’s important to note that not all AI is the same. In fact, there are many different types, and they are often built with certain purposes in mind. For instance, machine learning and generative AI (e.g., ChatGPT) are forms of black box AI which provide quick results to specific learnings/commands but provide little to no indication of how that result was reached. In these forms, there is justifiable concern for AI-related risks around data transparency, privacy, and security.
In contrast, Dayshape’s AI is built on a combinatorial optimisation model which provides clear reasoning behind AI-powered suggestions. Plus, significant enhancements have been made to Dayshape’s AI functionality and UI to further reduce the AI-related risks and enable users to unlock the full capabilities of AI across various use cases as illustrated below.
Users can adopt the benefits of AI, on their terms, by adjusting the level of AI support they need depending on the scheduling requirement.
Day to day, resource managers may want to use Dayshape Assist where they use AI-powered suitability scoring (considering availability, grade, location, or skills data from across the firm) to match the right resources to the right bookings.
However, for more complex resourcing requirements where the bigger picture needs to be considered, using a greater level of AI support would be more efficient. Using Dayshape Advise, our combinatorial optimisation- based AI performs scheduling suggestions across bulk workloads, leaving the resource managers to simply approve or reject the automated scheduling suggestions and apply them to the plan within an intuitive and transparent interface. Such flexibility drives more efficiency through AI, whilst leaving the control firmly in the hands of resource managers to determine when and how it’s applied.
With flexible levels of AI support provided, resource managers can review suggestions made, alongside the reasoning behind the suggestion. Hence providing resource managers with greater confidence in their data-driven resourcing decisions.
Dayshape’s AI is built to handle scale and complexity within resource management.
Whilst resource managers are key to making the strategic decisions within resource management, they simply can’t process the same amount of data, in the same amount of time, as AI can.
Similarly, as organisations input a greater depth of datapoints into resource management systems, this increases resourcing complexity. Hence making it increasingly difficult for resource managers to optimally schedule resources (and negate clashes) without some assistance from AI.
With the ability to produce resource suggestions holistically across all resource considerations and datapoints in seconds, Dayshape’s AI provides firms with optimised scheduling at scale.
In conclusion, to benefit from AI, firms must have a twofold approach. First, build a concrete understanding of AI and second, do the due diligence on AI providers to find low risk and pragmatic ways to apply it. Doing so will create trust within the firm and pave the way for new opportunities to work cohesively with AI.
With a flexible and transparent approach to AI, Dayshape provides firms with the ultimate ally to increase scheduling efficiencies. Available to use when needed and on your terms, discover more about Dayshape’s advanced AI functionality and improved UI.
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