FINAL WORD
coupled to business goals , but also imposes strict frameworks that ensure quality , privacy and security .
Sustainable success in AI requires a cultural shift . The CIO will be both AI champion and AI teacher , encouraging colleagues to look at data differently by highlighting the connection between it and business value . By promoting data fluency , the CIO becomes a value creator .
They will also engage with partners and peers to shape the market . They will make use of existing networks while creating new ones . Through this continuous learning , CIOs will improve their understanding of Generative AI and what their priorities should be to maximise its value-add .
Ron Beck , Marketing Strategy Director , AspenTech
Hybrid digital twin model
Digital twins have , to date , been most effectively implemented as high fidelity , granular models representing process units of high economic value . One innovation currently taking place is the merging of first principles models with AI-based models into digital twins known as hybrid models .
These hybrid models make it cheaper and easier to make models of more units , to provide much higher accuracy in reflecting the actual operating conditions of process units and can be continuously updated to mirror operations . Also , new data fabric technology is able to rapidly contextualize and aggregate data streams from assets to feed the needed real-time data to digital twins .
Transparent vendors
Within these knowledge-exchange networks , CIOs will find Generative AI vendors who will come under increasing pressure to be transparent about how their algorithms operate , going so far as to allow their customers to inspect them . That transparency must extend to clear explanations of where data is stored , sent , and processed .
And vendors will be expected to comment openly on how data can be managed within the complex and fast-moving regulatory environments we find in regions such as the GCC .
Generative AI represents an opportunity and a challenge for CIOs . Leaders must go back to the drawing board on data governance and put it front and centre . There is an opportunity for AI to play a role in data governance by continuously monitoring for potential vulnerabilities and operating autonomously to remedy them .
It appears as if Generative AI is not bound by limits in terms of what use cases it can satisfy . It will be up to the CIO to impose such limits in consultation with colleagues , as they decide where to deploy it , what roles should be reshaped , and what business processes should be optimised . The stakes are high .
Mastering the responsiveness-responsibility tradeoff means competitiveness and prosperity . Getting it wrong could mean the end of a brand . p
A hybrid model digital twin provides agility to change operations by allowing the testing of the impact of a changed operating strategy on the twin before making the change in the plant . This help less experienced operating workers make better decisions . Also , as more operating goals need to be balanced , digital twins enable better optimisation between margin , yield , quality , and emissions .
Two major challenges in implementing digital twins are , first , keeping the scope focused on manufacturing units where better operations will create economic value , and second , establishing processes for data cleaning to ensure that the digital twin ingests data that accurately reflects operating conditions .
A third challenge is implementing business processes to sustain digital twin models through ongoing training of operating staff , to ensure a solid understanding and trust in the digital technologies they are using , and to ensure trained technical SMEs are available to maintain the models in an evergreen condition . These business processes will be repaid through the operating insights , agility and benefits derived from the digital twins .
Some key skills required to achieve success with digital twin success include expertise in edge computing and connecting measurement and control data streams , as well as process historians to ensure that the data flows reliably to the digital twins . Data cleaning is another important skill . Also , another key skill is an effective before-and-after analysis to capture the value created by digital twins .
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