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Switzerland’s fastest-growing AI company Unit8 takes a look at the Swiss economy in 2023

According to Unit8, Swiss companies are preparing for tougher times: costs and processes are under scrutiny, including spending on IT infrastructure, cloud technologies, and AI & analytics initiatives. Nevertheless, with AI & analytics’s vast potential in delivering efficiency gains across an organisation’s value chain, AI & analytics should not be seen as a cost to be mitigated but rather as a strategic response to the incoming economic headwinds.

As an AI company operating throughout Switzerland, Unit8 gains insights into the challenges Swiss companies are struggling with on a daily basis. These include companies from tech-savvy sectors and ones where business models are not yet fully digitalized, such as chemicals, pharmaceuticals, banking, and finance. Thanks to these insights, Unit8 can foresee which topics will occupy the Swiss economy in the coming year.

In general, we see that the Swiss economy is negatively affected by the rising levels of inflation,

says Michal Rachtan, CTO and Co-Founder of Unit8. ‘Although effects in Switzerland are not as pronounced as in the eurozone, the rising cost of material, energy, and services is forcing companies to rethink their strategies.' This will be a defining topic of 2023, and large companies are preparing for more challenging times ahead, if not a recession. Processes are increasingly being examined for efficiency gains,’ says Michal Rachtan, ‘with a focus primarily placed on costs and the ROI of ongoing initiatives.’ That means operational use cases aiming to improve enterprise efficiency take priority over long-term innovation initiatives with uncertain chances of success.

Unimaginable in recent years, but necessary for corporations today: pragmatic decisions

From ‘nice to have’ to highly transformational, corporations are rigorously evaluating every project for its ROI and cash flow impact. This trend has been evident for the last few months and will continue into 2023. The project portfolio, including initiatives around digital and cloud transformation, is also under scrutiny. Expenditure on cloud technologies has constantly been growing over the last few years, fuelled by the promise of flexibility, reduced complexity, and limitless scalability. In some cases, those costs grew out of control. Companies ahead in a successful migration to the cloud are now trying to rationalise and cap those expenditures. The focus is shifting towards smart portfolio management of AI & analytics use cases, prioritising those which can bring short-term efficiency gains and improve a company’s financial position.

Avoid flying blind – with good data

Data and advanced analytics will play a central role in overcoming business challenges. Measuring performance is key to improving a company’s understanding of its business. High-quality data and robust metrics will be mission-critical in making the right decisions while addressing cost efficiencies. Good data insights can improve productivity, and resource and supply management, enhance an organisation’s flexibility and agility, and strengthen human resource planning.

‘However, for this to materialise in practice, data must be made accessible, especially for department heads in production and roles such as operations, marketing, and finance. There is increasing pressure for AI & analytics initiatives to graduate from being senior management’s pet projects to delivering real, measurable impact on an organisation’s bottom line at scale,’ says Rachtan.

As the current inflation in prices is increasing spending on materials and transportation, this is triggering an increased focus on cost efficiency. Advanced analytics can generate significant operational efficiencies; improving yields, avoiding material waste, postponing or eliminating capital expenditures, improving workflow efficiencies, and leading to improved production line outputs. Considerable efficiency gains can also be achieved in customer-facing areas via smart automation of selected customer service processes, e.g. automated insurance claim processing or basic customer requests via chatbots or voice bots.

Therefore, he expects continued investment in data analytics in the coming year, especially in the banking, financial services, and insurance sectors. In addition to customer support, fraud detection and employee efficiency are of primary importance in these sectors.

Michal Rachtan, CTO and Co-Founder


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