The report, which was published by Perception Point and Osterman Research this week, found that firms typically spend $1,197 per employee each year to deal with cybersecurity incidents, which can add up quickly over time. Because of this, Deloitte believes that employees and board members will be better equipped to thwart cyberattacks in 2023.
Moreover, Deloitte anticipates that securing emerging technologies, bolstering connected device visibility, and data security practices will be priorities for organizations in 2023. Security supply chains, in addition to security talent shortages and issues, are also likely to continue. The talent shortage, however, is likely to persist as security supply chains continue to struggle, the company leaders mentioned.
The experts predicted that future-forward preparedness and organizational resilience will play an important role in helping enterprises better manage their vulnerability to adversary actors in the future, in addition to cybersecurity.
Mulesoft, a Salesforce-owned company, also made predictions about the businesses in 2023. It noted that, up until now, companies have remained committed to digital transformation, speeded up by automation, composable agility, low-code, and no-code tools, data automation, and layered cyber defenses to continue to grow.
Quantum Growth
While tech giants like Google, IBM, Microsoft, and Intel made headlines this week, they are also pushing ahead with cloud services and other tools to test quantum algorithms.
Sandeep Pattathil, a senior analyst at IT advisory firm Everest Group, told VentureBeat that quantum computing’s algorithmic improvements will remain the biggest challenge. He said that IBM, Microsoft, and Google are all working on cloud services to test quantum algorithms. It will also be difficult for them to develop speedy quantum computing programs.
AI Needs Change
According to Kevin McNamara, CEO, and founder of synthetic data vendor, Parallel Domain, which just raised $30 million in a series B round led by March Capital, Artificial intelligence (AI) may be eating the world as we know it, but Ai itself is also starving — and needs to change its diet.
“Data is food for AI, but AI today is underfed and malnourished,” stated Kevin McNamara. “That’s why things are growing slowly. But if we can feed that AI better, models will grow faster and in a healthier way. Synthetic data is like nourishment for training AI.”
