(eng): In this note we consider Markov decision chains with finite state space and compact actions spaces where the stream of rewards generated by the Markov processes is evaluated by an exponential utility function (so-called risk-sensitive model) with a given risk sensitivity coefficient. If the risk sensitivity coefficient equals zero (risk-neutral case) we arrive at a standard Markov decision chain. Necessary and sufficient optimality conditions along with equations for average optimal policies both for risk-neutral and risk-sensitive models will be presented and connections and similarity between these approaches will be discussed.