Genera­tive AI is revolu­tio­ni­zing compa­nies: What impact do develo­p­ments have on strategic build vs. buy decis­ions

Genera­tive AI (Gen AI) has played a trans­for­ma­tive role in the world of techno­logy and business develo­p­ment in recent years. Compa­nies are faced with the chall­enge of adapting their strate­gies to keep pace with this rapid develo­p­ment. This article looks at the impact of GenAI develo­p­ments on build vs. buy decis­ions for organiza­tions. It is a summary of our master­class from the AI.Summit. If you would like to learn more, please contact us!

Impact of GenAI on build vs buy decision

1. accele­rated matura­tion time of AI

The develo­p­ment of AI has accele­rated drama­ti­cally in recent years, with genera­tive AI playing a leading role. From text genera­tion and image proces­sing to 3D and video produc­tion, results are being achieved that incre­asingly surpass the quality of human work.

Compa­nies need to recognize that AI is no longer just a comple­men­tary techno­logy, but a key driver of innova­tion and compe­ti­tive advan­tage. The ability to adapt these techno­lo­gies will be crucial to remain relevant in a rapidly changing market environ­ment.

2. the redefi­ni­tion of “build vs. buy

The intro­duc­tion of Gen AI has funda­men­tally changed the debate between in-house develo­p­ment and purcha­sing solutions.

In-house develo­p­ment (build): For compa­nies with a high level of AI maturity, this approach offers advan­tages such as complete control, IP owner­ship and the ability to develop custo­mized solutions that perfectly match indivi­dual requi­re­ments.

Buy: Compa­nies with less exper­tise can benefit from ready-made solutions that can be imple­mented more quickly and require less initial invest­ment. This is parti­cu­larly attrac­tive for compa­nies that want to benefit quickly from AI without tying up exten­sive resources.

The decision between “build” and “buy” depends heavily on the maturity and strategic goals of an organiza­tion. The right balance between control and effici­ency is crucial.

3. time and cost savings through genera­tive AI

Another advan­tage of Genera­tive AI is its ability to signi­fi­cantly reduce develo­p­ment times and costs. Compa­nies can shorten their project lead times by up to 24% and reduce costs by up to 18% at the same time.

This effici­ency enables compa­nies to achieve more while conser­ving resources. Whether start-up or estab­lished company: The economic benefits make the use of Gen AI attrac­tive for many compa­nies.

4. diverse appli­ca­tion possi­bi­li­ties in practice

The poten­tial appli­ca­tions of Gen AI extend across numerous indus­tries and functions. Here are a few examples:

• Product design and enginee­ring: Tools such as Figma AI enable the creation of innova­tive designs in the shortest possible time.
• Code genera­tion: GitHub Copilot enables develo­pers to work faster and more effici­ently.
• Marke­ting and customer service: Gen AI perso­na­lizes customer experi­ences and automates repeti­tive tasks, incre­asing effici­ency and customer satis­fac­tion.

These appli­ca­tions show that Genera­tive AI is far more than just a technical tool. It is an enabler that supports creative processes and makes day-to-day work easier.

Conclu­sion: utili­zing the poten­tial of Gen AI

The intro­duc­tion of genera­tive AI offers compa­nies the oppor­tu­nity to drive innova­tion and streng­then their market position. Be it to optimize processes, reduce costs or open up new markets: The key lies in a well thought-out strategy that is tailored to the company’s specific needs and capabi­li­ties.

Gen AI is not just a techno­logy of the future, but a techno­logy of the present that must be used now in order to be successful in the long term.