It's not (just) about technology.
Why aligning and integrating company culture and operations with AI needs is the first step to innovation

Is Artificial Intelligence a turnkey solution for business innovation? 
Absolutely yes, as long as it is backed by a clear strategic plan to support its adoption and incorporation into business processes: without this, investing considerable sums in AI-related solutions and skills simply becomes following a trend now considered a must for companies in every sector.

La questione in gioco è che, oggi, è realmente un obbligo investire in maniera strategica e sistemica nell’Artificial Intelligence e non per diventare il top leader “invincibile” all’interno del proprio mercato, ma, semplicemente, per restare all’interno di quel mercato. Ottimizzare la produttività, potenziare al massimo le competenze umane e gestire l’incertezza informativa del futuro “anticipando” servizi a valore, sono già oggi il motore chiave dei processi di innovazione e di crescita aziendale. 

The issue at stake is that, today, it is really an obligation to invest strategically and systemically in Artificial Intelligence and not to become the "invincible" top leader within one's market, but, simply, to stay within that market. Optimizing productivity, maximizing human skills, and managing the information uncertainty of the future by "anticipating" value services are already key drivers of business innovation and growth processes.

How then to embrace the AI revolution? 
More importantly, how to lead it without being overwhelmed by it?

Again, innovation is not (only) about technology. 
Companies that really want to embark on an Artificial Intelligence adoption journey must align and integrate the culture with its needs, through mandated steps:

• Develop a strategic plan: identifying specific use cases within the overall design, setting realistic expectations and creating a roadmap for implementation are the key steps to harness the potential of AI in line with business goals.

• Invest in Data Governance and Data Security: high quality data is a prerequisite for successful AI implementation. Companies must invest in data governance, making sure that data is accessible, well-organized, and protected.

• Fostering an AI "friendly" culture: encouraging curiosity, continuous learning and the desire for evolution of all team members are the basis of a collaborative environment among people with different skills, who actually build the corporate AI project together.

• Support cross-unit and cross-team collaboration: linking to the previous point, AI implementation should never be isolated to a single department or function, but always be the result of collaboration between various teams, from IT, marketing, operations to customer service, for more comprehensive and effective AI solutions that take into account all backend aspects and the entire customer lifecycle.

• Invest in continuous learning: AI is a rapidly evolving field; continuous training is essential so that everyone stays up-to-date on the latest opportunities and new areas of application.

• Managing ethical and regulatory issues: ensuring fairness, transparency, and compliance with relevant regulations to build trust with users and stakeholders by proactively addressing ethical and regulatory issues is a prerequisite obligation for AI adoption.

To achieve scalability and concrete results from AI investments, everyone within the company must open up to a new way of working and collaborating with others, on a path that will increasingly see decision-making democratized. In a data-driven society, people at all levels, top management first and foremost, have long been trusting the power of data, contributing to decision-making that is no longer dictated solely by their expertise and seniority, but supported by algorithms to be truly meaningful. 
This means that the direction in which we are heading, albeit for now still only ideally, is of organizations in which everyone will tend to have to be involved in decision making, from the entry-level employees working with data analytics to the business leaders.

Similarly, as with most technological innovations, Artificial Intelligence has greater impact when it is developed within cross-functional, interdisciplinary teams that have a diverse range of perspectives and expertise to activate to ensure that broader priorities in the business landscape, rather than isolated issues, are addressed.

Una riuscita implementazione dell'Artificial Intelligence richiede quindi un approccio strategico che vada oltre gli investimenti tecnologici e che sappia coinvolgere tutti gli attori in gioco...Perché se è vero che un tema critico è quello di una competizione essere umano-macchina vi sono i germogli per prospettare una maggiore vicinanza tra le persone, una rinnovata alleanza essere umano-essere umano per sfruttare al meglio le potenzialità di questa tecnologia restando protagonisti di questa rivoluzione senza precedenti. 

A successful implementation of Artificial Intelligence therefore requires a strategic approach that goes beyond technological investments and that knows how to involve all the players involved... For if it is true that a critical issue is that of a human being-machine competition there are the shoots to prospect for a greater closeness between people, a renewed human being-human being alliance to make the most of the potential of this technology while remaining protagonists of this unprecedented revolution.