Egypt’s AI champions could help drive economic leapfrogging: McKinsey partner

Egypt’s ability to build a competitive artificial intelligence industry will depend partly on local companies becoming successful adopters of generative AI, helping the country establish a track record that could support the export of AI-related skills and services, a McKinsey senior partner said Thursday.

Johannes-Tobias Lorenz said Egyptian companies that successfully integrate generative AI into their businesses could help position the country as a credible base for AI products and services in regional and global markets.

“You can sort of better sell a product or these kinds of services if you are recognised as a country where successful companies apply this very successfully,” Lorenz said in an interview with Amwal Al Ghad English on Thursday.

For Egypt to accelerate that process, the country will need continued investment in technology infrastructure and talent, as well as clarity that gives companies confidence when making investment decisions, he said.

Lorenz said infrastructure would provide the foundation for developing the industry, while Egypt’s talent pool offered an important opportunity.

Egypt’s talent an opportunity

Lorenz also highlighted Egypt’s talent base as a potentially important advantage, contrasting his observations in Egypt with what he described as a doomsday mood he has encountered in Europe.

“That was exciting for me as a European because there’s a bit of doomsday mood in Europe at the moment,” Lorenz said, referring to discussions around the future of work and technology.

He said he was struck by the pride Egyptian workers expressed in their work and by the enthusiasm surrounding AI.

“Every motivated talent wants to seize this opportunity, seize it as their path forward,” Lorenz said.

For Egypt to translate that talent into a sustainable AI industry, however, Lorenz said the country would need continued investment in technology infrastructure and talent, as well as clarity.

He said companies need “regulatory safety and clarity on what is required” so they have a clear foundation for making investment decisions and understand that the government is supportive of AI development.

That clarity becomes particularly important for large infrastructure investments, he said, where companies need greater certainty and less back-and-forth over requirements.

“Regulation, safety, talent, then the investments,” Lorenz said, adding that building out technology infrastructure, including cloud capacity, would also be important.

SMEs see opportunity

Small and medium-sized enterprises could also benefit from AI adoption, although they face different challenges from larger companies, Lorenz said.

McKinsey’s figures presented at the media roundtable did not include SMEs because they focused on leading companies in each category. However, Lorenz believes smaller businesses may have an advantage because they generally have “less internal complexity” and are often family-owned or directly led by their owners.

That can make it easier to take investment decisions and implement changes, Lorenz said.

The smaller scale of SMEs can also constrain their ability to invest in labour and find the right people, creating an opportunity for AI agents to help them expand their capabilities without requiring equivalent increases in staffing, he said.

“I assume those could be very helpful for growth,” Lorenz said.

CEOs shift from AI doubts to scaling

The concerns companies have about AI have also changed significantly, according to Lorenz.

Two or three years ago, executives were still questioning whether AI was simply a bubble. The focus has now shifted towards how to scale the technology while balancing investment in transformation with the pressure to deliver profitability from quarter to quarter, he said.

The challenge is particularly relevant for companies that need to make significant investments while continuing to meet short-term financial expectations.

Family-owned businesses can sometimes take a longer-term view, Lorenz said, allowing them to accept lower profits temporarily in exchange for investment in future growth.

Publicly listed companies can face greater pressure to deliver dividends and improve operating profits in the short term, he said.

AI adoption spreads, but impact remains concentrated

The comments came as McKinsey presented its latest findings on the rapid expansion of AI adoption and the gap between widespread use of the technology and its measurable economic impact.

About 87 per cent of companies surveyed are working with AI, but only 6 per cent have reached a level where AI is making a significant difference to their profit and loss accounts, Lorenz said during the briefing.

Around 37 per cent of companies have reported a significant or relevant contribution from AI to EBITDA, he said.

For Egypt, companies that become successful early adopters could potentially gain a competitive advantage over businesses in the region and elsewhere, Lorenz said.

The strongest-performing companies surveyed by McKinsey are seeing attractive returns from their AI investments, with many reporting payback periods of less than two years, he said.

That compares with investment horizons of three to five years that were more typical of earlier digital transformation projects.

AI moves into the workforce

AI is also evolving from a tool that employees use into something that can become part of the workforce itself, particularly as companies deploy agentic AI systems capable of performing tasks and solving problems with limited human intervention, Lorenz said.

McKinsey research presented at the briefing estimates that 57 per cent of tasks performed in companies could potentially be automated.

Lorenz stressed that this does not mean 57 per cent of jobs would disappear because individual jobs typically comprise multiple tasks.

Instead, companies could redesign roles and use productivity gains to improve services, support growth, or address workforce shortages, he said.

Robotic AI could be next wave

AI adoption is currently strongest in areas including IT, knowledge management, and software engineering, according to McKinsey findings.

Manufacturing, supply-chain, and inventory management have seen less adoption so far, but robotic AI could become the next major wave as machines become capable of performing increasingly sophisticated physical tasks, Lorenz said.

For companies, the transition will require investment in data, technology, talent, and operating models, alongside a gradual expansion of AI capabilities.

Companies will also need to account for the rising cost of AI usage. While the price of individual AI tokens has generally fallen as models have improved, increased usage has pushed overall spending at some companies above initial expectations, Lorenz said.

The broader challenge, he said, is to build AI capabilities at sufficient scale without either moving too slowly or attempting an overly broad transformation all at once.

Companies need to redesign processes, not just add AI

Lorenz said the companies generating the greatest impact from AI are not simply inserting AI tools into existing workflows.

Instead, they are stepping back to reconsider what customers need, how their products and services are delivered and how the underlying business processes should be redesigned.

Companies that simply replace individual steps in an existing workflow with AI tools risk capturing only limited benefits, he said.

The more successful approach is to start with the customer and value proposition, then redesign products and processes around the new capabilities AI provides.

Companies will also need to develop capabilities spanning data, technology, talent and operating models, while ensuring employees and customers actually adopt the resulting systems.

Lorenz said businesses should avoid both an overly incremental approach and a “big bang” transformation, instead building capabilities and infrastructure that can be replicated across different business areas and use cases.

For Egypt, that combination — motivated talent, infrastructure investment, regulatory clarity and successful local adopters — could help turn AI from an emerging technology into a broader source of competitiveness and export potential.