Leadership in the Age of AI:
People Make the Difference

What can deci­sion-makers use as a guide today when faced with the task of lead­ing their compa­ny into the AI era?

Lead­er­ship in the Age of AI: After all, Arti­fi­cial Intel­li­gence has well arrived in the construc­tion and prop­er­ty sector too – as a compet­i­tive factor and a tool, as well as a compo­nent of smart build­ings and neigh­bour­hoods. At the same time, it presents managers and employ­ees alike with a complete­ly new situ­a­tion. After all, high­ly devel­oped AI agents feel hard­ly any differ­ent from human colleagues in oper­a­tional settings. In this Lead­er­ship Impulse, we present key insights and prac­ti­cal approach­es on how compa­nies can success­ful­ly intro­duce AI with­out losing sight of people’s legit­i­mate interests.

Known and hidden challenges

The use of AI presents managers with a range of chal­lenges. Some of these are well-known – such as the rapid pace of tech­no­log­i­cal devel­op­ment and the ques­tion­able reli­a­bil­i­ty of results. Added to this are a lack of special­ists or exper­tise with­in compa­nies, as well as employ­ees’ fears of job loss­es. Howev­er, managers should also address less obvi­ous factors in order to achieve effi­cient use of AI with­in the company:

• Over­es­ti­mat­ed skills
  Accord­ing to a study by Skill­soft¹ , managers are often poor­ly informed about which AI skills are actu­al­ly present with­in their teams. Only 18 per cent of the compa­nies surveyed system­at­i­cal­ly assess such skills. Howev­er, employ­ees often tend to over­es­ti­mate their own abil­i­ties in this area. This can lead to compa­nies invest­ing in ambi­tious AI projects only to realise halfway through that their own capa­bil­i­ties are not suffi­cient for implementation.
• Shad­ow AI
  An effi­cient AI roll­out can also be hampered by so-called shad­ow AI. This refers to the use of AI tools such as Chat­G­PT or Gemi­ni with­out offi­cial approval or over­sight by the compa­ny, often via private accounts and devices. Accord­ing to a bitkom study², around 40% of compa­nies in Germany assume that employ­ees use shad­ow AI – and the trend is rising. This not only creates secu­ri­ty risks. ‘Proven’ shad­ow solu­tions can also reduce will­ing­ness to switch to approved but new, unfa­mil­iar AI systems.

Manag­ing hybrid teams of humans and AI

Today, agent-based AI acts autonomous­ly, uses tools and inter­acts with other systems. This means that managers are faced with the task of deploy­ing and manag­ing AI agents effec­tive­ly, along­side human staff. A study by Deloitte³has iden­ti­fied a number of prereq­ui­sites for this:

• Data liter­a­cy
  Data liter­a­cy is a good exam­ple of poly­math­ic lead­er­ship . It refers to the abil­i­ty to under­stand and use data “to iden­ti­fy prob­lems, find data-driven solu­tions and make predic­tions for the future.”
• Crit­i­cal thinking
  The quick, well-formu­lat­ed answers provid­ed by AI can easi­ly lead to a decline in one’s own crit­i­cal think­ing. It is there­fore neces­sary to have the abil­i­ty and will­ing­ness to ‘ques­tion answers, recog­nise bias’ and also crit­i­cal­ly exam­ine deci­sions made by AI that appear logical.
• Self-effi­ca­cy
  In view of increas­ing­ly power­ful AI systems, it is impor­tant to main­tain confi­dence in one’s own abil­i­ties. To this end, managers can lead by exam­ple with­in the organ­i­sa­tion, “provid­ing exam­ples of AI usage and shar­ing their own learn­ing process­es in deal­ing with this tech­nol­o­gy.” Employ­ees should be given the oppor­tu­ni­ty to “gain prac­ti­cal expe­ri­ence with AI” and thus boost their self-effi­ca­cy through posi­tive experiences.
• Digi­tal ethics 
  The study describes taking ethi­cal issues surround­ing AI use into account – such as avoid­ing bias or respect­ing copy­right – as a “key compe­tence for lead­ers”. This includes “not only tech­ni­cal know-how, but also a deep under­stand­ing of the digi­tal ethi­cal impli­ca­tions and impacts.”

Shap­ing the success­ful use of AI 

In the latest “Glob­al Human Capi­tal Trends” study⁴, Deloitte describes how compa­nies can address the chal­lenges posed by AI and use them to their advan­tage. The start­ing point is the obser­va­tion that, with the devel­op­ment of AI, three deci­sive turn­ing points have now been reached:

• “Human plus machine” is becom­ing “human times machine”. Added value is creat­ed by consis­tent­ly align­ing organ­i­sa­tions and process­es with collab­o­ra­tion with AI.
• Savings from effi­cient AI inte­gra­tion should be contin­u­ous­ly rein­vest­ed in in-house capa­bil­i­ties to keep pace with tech­no­log­i­cal developments.
• Agile, dynam­ic learn­ing and work­ing are replac­ing fixed plans and procedures.

To this end, the study has iden­ti­fied seven factors that make work­ing with AI successful:

1. Inte­gra­tion: ‘Human and Machine’
   Where AI is mere­ly incor­po­rat­ed into exist­ing work­flows, its bene­fits are limit­ed. The added value of AI is great­est when process­es, tools and roles are consis­tent­ly aligned with this way of work­ing – with suffi­cient train­ing, clear rules and commit­ted leadership.
2. Data qual­i­ty and controlled processes
   Compa­nies need process­es and controls that prevent or filter out inac­cu­rate and incor­rect AI results. This can be achieved, for exam­ple, through a thor­ough check of the input data, logging of deci­sion-making steps, as well as risk assess­ments and stress tests.
3. Rules govern­ing the respon­si­bil­i­ties of humans and machines
   AI enables faster and more informed deci­sions, but respon­si­bil­i­ty remains with humans. Managers should there­fore always be able to assess the thought process­es of an AI and guide it as a digi­tal ‘colleague’.
4. A bind­ing corpo­rate culture 
   In addi­tion to the ‘human-machine’ approach, consid­er­a­tion should also be given to how people inter­act: for exam­ple, how do we deal with errors result­ing from AI actions? Bind­ing rules are need­ed to safe­guard the culture of inter­ac­tion with­in the company.
5. Adap­ta­tion as a perma­nent state
   At the oper­a­tional level, AI makes many things avail­able almost instant­ly that used to take weeks. Compet­i­tive advan­tages arise when compa­nies devel­op agile capa­bil­i­ties and struc­tures to support this, with­out losing sight of their goals and principles.
6. Flex­i­ble roles for an agile organisation
   Tradi­tion­al func­tions with­in compa­nies are designed for consis­tent roles. Some, such as Control­ling, will remain. Howev­er, many areas will require a more flex­i­ble approach in the future. Exam­ples include strate­gic plan­ning, project devel­op­ment or the use of AI itself. We recent­ly intro­duced such a role in the Valdivia News­room: the Chief Talent Trans­for­ma­tion Offi­cer (CTTO).
7. Contin­u­ous learning 
   Sugges­tions and tools for contin­u­ous learn­ing empow­er employ­ees to find their way in the AI-inte­grat­ed world of work. These include, amongst other things, labs for test­ing new ideas and appli­ca­tions, peer-to-peer learn­ing with­in teams, learn­ing and coach­ing AIs, and projects that combine work and learning.

Conclu­sion – People make the difference 

In the conclud­ing chap­ter, the study outlines the conclu­sions that can be drawn from the observed factors, partic­u­lar­ly for decision-makers:

• To work with AI, compa­nies need well-thought-out process­es that incor­po­rate both humans and machines, util­is­ing their respec­tive strengths. This creates genuine added value, fosters inno­va­tion and, at the same time, preserves the value of human skills in the workplace.
• The use of AI requires a compe­tent data regime that priori­tis­es trans­paren­cy and accu­ra­cy. This strength­ens trust in both human and digi­tal decisions.
• Under compe­tent, ethi­cal­ly respon­si­ble lead­er­ship, AI enhances human capa­bil­i­ties. Its speed aids deci­sion-making with­out under­min­ing human agency. There­fore, AI should always be embed­ded with­in the company’s culture. In this way, it can foster a sense of belong­ing and inclu­sion and strength­en the organisation’s social fabric.
• Where mean­ing­ful­ness, trust and human strengths are inte­grat­ed into work­ing with AI, this strength­ens the company’s resilience and success bene­fits everyone.
• Contin­u­ous profes­sion­al devel­op­ment enables special­ists to tap into new oppor­tu­ni­ties whilst remain­ing rele­vant experts. In this way, progress remains recog­nis­ably linked to confi­dence in their abil­i­ties. On this basis, more creative and resilient teams emerge, which grow along­side the tech­nol­o­gy rather than being displaced by it.

The key find­ing of the Deloitte study is that tech­nol­o­gy alone is not enough for a compa­ny to stand out and succeed in a compet­i­tive market. It is people who make the differ­ence – through creativ­i­ty, sound judge­ment and empathy.

Sources

1. “2025 Glob­al Skills Intel­li­gence Survey”, Skill­Soft, Septem­ber 2025
2. “Employ­ees are increas­ing­ly using shad­ow AI”, Bitkom Research, Octo­ber 2025
3. “From Reac­tion to Action: Lead­ing in the Age of GenAI”, Deloitte, May 2024
4. “2026 Glob­al Human Capi­tal Trends: From tension to tipping points – choos­ing the human advan­tage”, Deloitte Insights, March 2026

(Image source: istockphotos.com)