Most organisations are in the early stages of generative AI adoption, but within a remarkably short space of time, the technology will likely disrupt organisational structures, hierarchies and jobs.
So says Anton Kopytov, Digital Transformation and Business Development Leader at CloudSmiths, a Digicloud partner. CloudSmiths is a tech consultancy with a special focus on data analytics, machine learning, cloud infrastructure and business reporting, and has run scores of GenAI workshops for clients in recent months.
“GenAI's progress is remarkable. While widespread disruption might take a few years, its impact is undeniable. Savvy businesses are building the foundation: strong infrastructure, cloud expertise, data strategy and a GenAI-ready workforce. By understanding use cases and limitations, these companies will be poised to leverage GenAI for high-impact applications, democratising data-driven decisions,” he says. “It’s democratising every aspect of life, from how we build code and use data, to how we provide customer support and service and run organisations.”
He emphasises that a strong business foundation is required to capitalise on GenAI.
"GenAI is a disruptive technology with immense potential for businesses. We're in the early stages of adoption, where companies are actively learning its capabilities and best practices. This includes developing expertise in areas like stakeholder understanding, project structures for swift value delivery and establishing a strong foundation. Companies that grasp these elements will be well-positioned to leverage Gen AI for high-impact applications," Kopytov says.
“The organisations we deal with understand that the approaches and hierarchies they had before the GenAI era arrived aren’t necessarily effective to manage the disruption GenAI brings. Some are now piloting different models, such as centralised structures to incubate knowledge and train the organisation. These new centres of excellence may later decentralise. The question is when to split centres of excellence into a federated model to avoid them becoming a bottleneck.”
Kopytov says that to fully harness the potential of GenAI, organisations will have to review their operational, technical and data infrastructures, consider how to operate and maintain applications based on AI, and ensure they have the necessary high-quality data to inform the models.
He adds: “There are also operational and managerial aspects – what teams should be tasked with building AI, as well as governance including security, compliance and ethics. There are many moving parts and most are moving asynchronously and at different paces. Setting up organisational structures to capture the full value of GenAI may take time.”
Google pioneers revolutionary GenAI
Kopytov highlights Gemini, Google's next chapter of GenAI, as an example of the rapid pace of innovation. Gemini is described as the most capable and general model Google has ever built, and it is the result of large-scale collaborative effort by teams across Google, including Google DeepMind and Google Research.
Kopytov describes Google’s latest next-generation release – Gemini 1.5 Pro – as nothing short of amazing. In this model, Google has significantly increased the amount of information it can process – running up to 1 million tokens consistently. Google reports that this is the longest context window of any large-scale foundation model yet. Gemini 1.5 has a new Mixture-of-Experts (MoE) architecture and optimisations to reduce latency and computational requirements and enhance the user experience.
Gemini 1.0 Ultra for Google Workspace, available as an add-on solution via DigiCloud partners, brings GenAI to boost productivity across Workspace business and collaboration tools. With seamless integration and the ability to understand and respond to a diverse set of inputs, Gemini includes enterprise-grade data protection. Its features include writing assistance and proofreading in Google Docs and Gmail, design generation and support in Google Slides, organisational support such as custom tables and task trackers in Google Sheets, and studio lighting and sound and translated captions for video calls. Admins can set up AI classifications of sensitive data to automatically apply labels to new and existing files in Google Drive.
Kopytov says: “The Gemini for Workspace cost model in terms of benefits such as transcripts of text of video conferences and calls, summarising discussions and setting tasks, is amazing. At the price point Google offers, it is very competitive versus other enterprise solutions. Gemini’s new abilities to support presentations, and helping people analyse and summarise content, will disrupt many processes and jobs in many sectors.”
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